Dissertations / Theses: 'Autonomous robots; Path planning'

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Crous, C. B. "Autonomous robot path planning." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/2519.

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Thesis (MSc (Mathematical Sciences. Computer SCience))--University of Stellenbosch, 2009. In this thesis we consider the dynamic path planning problem for robotics. The dynamic path planning problem, in short, is the task of determining an optimal path, in terms of minimising a given cost function, from one location to another within a known environment of moving obstacles. Our goal is to investigate a number of well-known path planning algorithms, to determine for which circumstances a particular algorithm is best suited, and to propose changes to existing algorithms to make them perform better in dynamic environments. At this stage no thorough comparison of theoretical and actual running times of path planning algorithms exist. Our main goal is to address this shortcoming by comparing some of the wellknown path planning algorithms and our own improvements to these path planning algorithms in a simulation environment. We show that the visibility graph representation of the environment combined with the A* algorithm provides very good results for both path length and computational cost, for a relatively small number of obstacles. As for a grid representation of the environment, we show that the A* algorithm produces good paths in terms of length and the amount of rotation and it requires less computation than dynamic algorithms such as D* and D* Lite.

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Schmitt, Paul Richard. "Reactive path shaping : local path planning for autonomous mobile robots in aisles." Thesis, Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/17778.

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balakrishnan, mohanakrishnan. "COVERAGE PATH PLANNING AND CONTROL FOR AUTONOMOUS MOBILE ROBOTS." Master's thesis, University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2769.

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Coverage control has many applications such as security patrolling, land mine detectors, and automatic vacuum cleaners. This Thesis presents an analytical approach for generation of control inputs for a non-holonomic mobile robot in coverage control. Neural Network approach is used for complete coverage of a given area in the presence of stationary and dynamic obstacles. A complete coverage algorithm is used to determine the sequence of points. Once the sequences of points are determined a smooth trajectory characterized by fifth order polynomial having second order continuity is generated. And the slope of the curve at each point is calculated from which the control inputs are generated analytically. Optimal trajectory is generated using a method given in research literature and a qualitative analysis of the smooth trajectory is done. Cooperative sweeping of multirobots is achieved by dividing the area to be covered into smaller areas depending on the number of robots. Once the area is divided into sub areas, each robot is assigned a sub area for cooperative sweeping. M.S. Department of Electrical and Computer Engineering Engineering and Computer Science Electrical Engineering

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Qin, Caigong. "A computational framework for manipulator motion planning." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362068.

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Cowlagi, Raghvendra V. "Hierarchical motion planning for autonomous aerial and terrestrial vehicles." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41066.

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Autonomous mobile robots - both aerial and terrestrial vehicles - have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical separation suffers a serious drawback: the geometric path planner has no information of the kinematic and dynamic constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates altogether the geometric planner by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematic model. In this thesis, we propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. We show that the proposed motion planning approach offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning. Finally, we propose a multi-resolution implementation of the proposed motion planner, which requires accurate descriptions of the environment and the vehicle only for short-term, local motion planning in the immediate vicinity of the vehicle.

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Hasler, Michael Douglas. "Simulation for Improvement of Dynamic Path Planning in Autonomous Search and Rescue Robots." Thesis, University of Canterbury. Electrical and Computer Engineering, 2009. http://hdl.handle.net/10092/4475.

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To hasten the process of saving lives after disasters in urban areas, autonomous robots are being looked to for providing mapping, hazard identification and casualty location. These robots need to maximise time in the field without having to recharge and without reducing productivity. This project aims to improve autonomous robot navigation through allowing comparison of algorithms with various weightings, in conjunction with the ability to vary physical parameters of the robot and other factors such as error thresholds/limits. The lack of a priori terrain data in disaster sites, means that robots have to dynamically create a representation of the terrain from received sensor range-data in order to path plan. To reduce the resources used, the affect of input data on the terrain model is analysed such that some points may be culled. The issues of identifying hazards within these models are considered with respect to the effect on safe navigation. A modular open-source platform has been created which allows the automated running of experimental trials in conjunction with the implementation and use of other input types, node networks, or algorithms. Varying the terrains, obstacles, initial positions and goals, which a virtual robot is tasked with navigating means that the design, and hence performance, are not tailored to individual situations. Additionally, this demonstrates the variability of scenarios possible. This combination of features allows one to identify the effects of different design decisions, while the use of a game-like graphical interface allows users to readily view and comprehend the scenarios the robot encounters and the paths produced to traverse these environments. The initially planned focus of experimentation lay in testing different algorithms and various weightings, however this was expanded to include different implementations and factors of the input collection, terrain modelling and robot movement. Across a variety of terrain scenarios, the resultant paths and status upon trial completion were analysed and displayed to allow observations to be made. It was found that the path planning algorithms are of less import than initially believed, with other facets of the robotic system having equally significant roles in producing quality paths through a hazardous environment. For fixed view robots, like the choice used in this simulator, it was found that there were issues of incompatibility with A* based algorithms, as the algorithm’s expected knowledge of the areas in all directions regardless of present orientation, and hence they did not perform as they are intended. It is suggested that the behaviour of such algorithms be modified if they are to be used with fixed view systems, in order to gather sufficient data from the surroundings to operate correctly and find paths in difficult terrains. A simulation tool such as this, enables the process of design and testing to be completed with greater ease, and if one can restrain the number of parameters varied, then also with more haste. These benefits will make this simulation tool a valuable addition to the field of USAR research.

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Haight, Timothy A. "Layered path planning for an autonomous mobile robot." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA286138.

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Thesis (M.S. in Computer Science and M.S. in Mathematics) Naval Postgraduate School, September 1994. Thesis advisor(s): Yutaka Kanayama, Craig W. Rasmussen. "September 1994." Bibliography: p. 43-44. Also available online.

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Selin, Magnus. "Efficient Autonomous Exploration Planning of Large-Scale 3D-Environments : A tool for autonomous 3D exploration indoor." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-163329.

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Exploration is of interest for autonomous mapping and rescue applications using unmanned vehicles. The objective is to, without any prior information, explore all initially unmapped space. We present a system that can perform fast and efficient exploration of large scale arbitrary 3D environments. We combine frontier exploration planning (FEP) as a global planning strategy, together with receding horizon planning (RH-NBVP) for local planning. This leads to plans that incorporate information gain along the way, but do not get stuck in already explored regions. Furthermore, we make the potential information gain estimation more efficient, through sparse ray-tracing, and caching of already estimated gains. The worked carried out in this thesis has been published as a paper in Robotand Automation letters and presented at the International Conference on Robotics and Automation in Montreal 2019.

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Hernández, Vega Juan David. "Online path planning for autonomous underwater vehicles under motion constraints." Doctoral thesis, Universitat de Girona, 2017. http://hdl.handle.net/10803/457592.

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The most common applications of autonomous underwater vehicles (AUVs) include imaging and inspecting different kinds of structures on the sea. Most of these applications require a priori information of the area or structure to be inspected, either to navigate at a safe and conservative altitude or to 2/2 pre-calculate a survey path. However, there are other applications where it's unlikely that such information is available (e.g., exploring confined natural environments like underwater caves). In this respect, this thesis presents an approach that endows an AUV with the capabilities to move through unexplored environments. To do so, it proposes a computational framework for planning feasible and safe paths online. This approach allows the vehicle to incrementally build a map of the surroundings, while simultaneously (re)plan a feasible path to a specified goal. The framework takes into account motion constraints in planning feasible paths, i.e., those that meet the vehicle's motion capabilities Les aplicacions més comunes dels vehicles autònoms submarins o AUVs són l’obtenció d'imatges i inspecció de diferents tipus d'estructures, com per exemple, cascos de vaixells o estructures naturals en el fons marí. Moltes d'aquestes aplicacions requereixen informació a priori de l'àrea o estructura que es vol inspeccionar. No obstant, existeixen aplicacions similars o noves, com l'exploració d'entorns naturals confinats (e.g., coves submarines), on aquesta informació pot ser inexistent. En aquest sentit, aquesta tesi presenta una alternativa per dotar un AUV amb l'habilitat de moure’s a través d'entorns no explorats. Per aconseguir aquesta fita, aquesta tesi proposa un mètode per calcular en temps real camins factibles i segurs. El mètode proposat permet al vehicle construir de forma incremental un mapa de l'entorn, i al mateix temps replanificar un camí factible cap a l'objectiu establert. El mètode proposat te en compte les restriccions de moviment del vehicle per planificar camins que siguin factibles

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Moletta, Marco. "Path planning for autonomous aerial robots in unknown underground zones optimized for vertical tunnels exploration." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-285574.

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Robotics is revolutionizing the work in dangerous environments like mines and tunnels, making life easier and safer for the workers. The specific case considered in this thesis regards UAVs used for 3D mapping of these zones. However, the use of UAVs in underground mines can be challenging for many reasons, such as reduced visibility, no GPS localization available and limited wireless communication, challenges that can be partially solved by using au- tonomous robots. Precisely for these reasons, this work aims to contribute on this application with the implementation of an autonomous path planning algorithm for aerial vehicles in underground zones.However, the peculiar contribution of this work regards shaft mines, which are vertical or near-vertical tunnels with access from the top and the bottom. This particular scenario is extremely challenging for UAVs, since the length of these tunnels (typically 100-200 m) cause the lost of signal from the con- trol station during the mission. Hence, the implemented algorithm is chosen in order to succeed in shaft scenarios. Then, an optimization of the algorithm has been made in order to decrease the time of the mission, thus increasing the chances of success by saving the battery of the robot. Robotik revolutionerar arbetet i farliga miljöer som gruvor och tunnlar, vilket gör livet enklare och säkrare för arbetarna. Det specifika fallet som behandlas i denna avhandling gäller UAV: er som används för 3D-kartläggning av dessa zoner. Användningen av UAV i underjordiska gruvor kan dock vara utmanan- de av många anledningar, till exempel minskad sikt, ingen GPS-lokalisering tillgänglig och begränsad trådlös kommunikation, utmaningar som delvis kan lösas genom att göra roboten autonom. Just av dessa skäl syftar detta arbe- te till att bidra till denna applikation med implementeringen av en autonom vägplaneringsalgoritm för flygfordon i underjordiska zoner. Det relaterade ar- betet har utvecklats med stöd av Inkonova AB, ett robotföretag i Stockholm. Emellertid gäller det speciella bidraget till detta arbete axelminor, som är ver- tikala eller nästan vertikala tunnlar med åtkomst från toppen och botten. Det- ta speciella scenario är extremt utmanande för UAV: er, eftersom längden på dessa tunnlar (vanligtvis 100-200 m) orsakar förlorad signal från kontroll- stationen under uppdraget. Därför väljs den implementerade algoritmen för att lyckas i axelscenarier. Sedan har en optimering av algoritmen gjorts för att minska uppdragstiden och därmed öka chanserna för framgång genom att spara i robotens batteri.

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Galceran, Yebenes Enric. "Coverage path planning for autonomous underwater vehicles." Doctoral thesis, Universitat de Girona, 2014. http://hdl.handle.net/10803/133832.

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This thesis proposes new methods to find collision-free paths allowing an AUV to cover an area of the ocean floor with its sensors, which is known as coverage path planning. First, we propose a coverage path planning method to plan 2D, safe-altitude surveys which provides a principled way to account for obstacles in AUV survey planning. Its main advantage is that it minimizes redundant coverage when the vehicle navigates at constant depth, leading to shorter paths. Second, we provide a method to account for the uncertainty in the vehicle position estimates when planning 2D surveys. The method minimizes the uncertainty induced by the path and leads to better maps of the ocean floor as a result. Third, we provide a coverage path planning method suitable for inspecting areas of the ocean floor including 3D structures. The resulting coverage paths enable applications requiring close proximity and allow viewpoints for full 3D sensing of the structure. Moreover, by contrast to most existing methods, we provide two techniques to adapt the planned path in realtime using sensor information acquired on-line during the mission, rather than only planning the path off-line and relying on the unrealistic assumption of an idealized path execution by the AUV. The proposed methods are validated in simulation and in experiments with a real-world AUV Aquesta tesi proposa nous mètodes per generar camins lliures de col·lisions per a vehicles submarins autònoms que permeten cobrir una àrea del fons de l'oceà usant els sensors del vehicle, tasca coneguda com a planificació de camins de cobertura. Primer, proposem un mètode de planificació de camins de cobertura per a planificar missions en un espai 2D a una altitud segura, proporcionant una manera fonamentada de tenir en compte obstacles en la planificació de missions per a vehicles submarins autònoms. L'avantatge principal del mètode proposat és que minimitza la cobertura redundant sorgida quan el vehicle navega a profunditat constant, obtenint camins més curts com a resultat. Segon, presentem un mètode per tenir en compte la incertesa de les estimacions de posició del vehicle durant la planificació de missions 2D. Aquest mètode minimitza la incertesa induïda pel camí i genera mapes més acurats del fons oceànic com a resultat. Tercer, presentem un mètode de planificació de camins de cobertura adequat per inspeccionar àrees del fons oceànic amb estructures 3D. Els camins de cobertura resultants permeten tasques que requereixen proximitat al fons i permeten una completa percepció 3D de les estructures d'interès. A més, a diferència de la majoria dels mètodes existents, proporcionem dues tècniques per adaptar els camins planificats en temps real utilitzant informació sensorial adquirida durant la missió, per contra de planificar només abans de l'execució de la missió i confiar en la poc realista assumpció d'una execució idealitzada del camí per part del vehicle. Els mètodes proposats han estat validats en simulació i en experiments amb un vehicle submarí autònom real

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Chow, Terence Y. (Terence Yuet-Wei). "Software architecture, path planning, and implementation for an autonomous robot." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/38149.

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Razavian, Adam A. "Cognitive Based Adaptive Path Planning Algorithm for Autonomous Robotic Vehicles." NSUWorks, 2004. http://nsuworks.nova.edu/gscis_etd/793.

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Processing requirement of a complex autonomous robotic vehicle demands high efficiency in algorithmic and software execution. Today's advanced computer hardware technology provides processing capabilities that were not available a decade ago. There are still major space and time limitations on these technologies for autonomous robotic applications. Increasingly, small to miniature mobile robots are required for reconnaissance, surveillance, and hazardous material detections for military and industrial applications. The small sized autonomous mobile robotic applications have limited power capacity as well as memory and processing resources. A number of algorithms exist for producing optimal traverses given changing arc costs. One algorithm stands out as the most used algorithm in simple path finding applications such as games, named the A * algorithm. This dissertation investigated the hypothesis that cognitive based adaptive path planning algorithms are efficient. This assumption is based on the observed capability of biological systems, which ignore irrelevant information and quickly process non-optimum but efficient paths. Path planning function for all organisms from insects to humans is a critical function of survival, and living organisms perform it with graceful accuracy and efficiency. This hypothesis was tested by developing a Cognitive Based Adaptive Path Planning Algorithm (CBAPPA) and a limited simulation program to test the theory of the algorithm, and comparing the result with other known approaches. This dissertation presented a new cognitive based approach in solving the path planning problems for autonomous robotic applications. The goal of this paper was to show that adaptive cognitive based techniques are more efficient by comparing this paper's path planning approach to analytical and heuristic algorithms. This study presented a two-step methodology of Primary Path and Refined Path. Each step was implemented by a number of heuristic algorithms. This paper illustrated that the CBAPPA’s path-finding efficiency exceeds the efficiency of some popular analytical and heuristic approaches. This research paper concluded that the hypothesis was verified and cognitive based path planning algorithm is efficient and is a viable approach for autonomous robotic applications.

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Rajasingh, Joshua. "Lane Detection and Obstacle Avoidance in Mobile Robots." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1288980793.

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Larkin, Susan M. "Wheeled autonomous mobile robots for use in harsh environments : a survey of recent publications /." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-01312009-063343/.

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Sylvester, Chadwick Allen. "Path planning and control of a nonholonomic autonomous robotic system for docking." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0002830.

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Tang, Robert. "A Semi-autonomous Wheelchair Navigation System." Thesis, University of Canterbury. Mechanical Engineering, 2012. http://hdl.handle.net/10092/6472.

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Many mobility impaired users are unable to operate a powered wheelchair safely, without causing harm to themselves, others, and the environment. Smart wheelchairs that assist or replace user control have been developed to cater for these users, utilising systems and algorithms from autonomous robots. Despite a sustained period of research and development of robotic wheelchairs, there are very few available commercially. This thesis describes work towards developing a navigation system that is aimed at being retro-fitted to powered wheelchairs. The navigation system developed takes a systems engineering approach, integrating many existing open-source software projects to deliver a system that would otherwise not be possible in the time frame of a master's thesis. The navigation system introduced in this thesis is aimed at operating in an unstructured indoor environment, and requires no a priori information about the environment. The key components in the system are: obstacle avoidance, map building, localisation, path planning, and autonomously travelling towards a goal. The test electric wheelchair was instrumented with the following: a laptop, a laser scanner, wheel encoders, camera, and a variety of user input methods. The user interfaces that have been implemented and tested include a touch screen friendly graphical user interface, keyboard and joystick.

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Walker, Ross. "Autonomous robot navigation through a crowded and dynamic environment : using a novel form of path planning to demonstrate consideration towards pedestrians and other robots." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/18833/.

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This thesis presents a novel path planning algorithm for robotic crowd navigation through a pedestrian environment. The robot is designed to negotiate its way through the crowd using considerate movements. Unlike many other path planning algorithms, which assume cooperation with other pedestrians, this algorithm is completely independent and requires only observation. A considerate navigation strategy has been developed in this thesis, which utilises consideration as an directs an autonomous mobile robot. Using simple methods of predicting pedestrian movements, as well as simple relative distance and trajectory measurements between the robot and pedestrians, the robot can navigate through a crowd without causing disruption to pedestrian trajectories. Dynamic pedestrian positions are predicted using uncertainty ellipses. A novel Voronoi diagram-visibility graph hybrid roadmap is implemented so that the path planner can exploit any available gaps in between pedestrians, and plan considerate paths. The aim of the considerate path planner is to have the robot behave in specific ways when moving through the crowd. By predicting pedestrian trajectories, the robot can avoid interfering with them. Following preferences to move behind pedestrians, when cutting across their trajectories; to move in the same direction of the crowd when possible; and to slow down in crowded areas, will prevent any interference to individual pedestrians, as well as preventing an increase in congestion to the crowd as a whole. The effectiveness of the considerate navigation strategy is evaluated using simulated pedestrians, multiple mobile robots loaded with the path planning algorithm, as well as a real-life pedestrian dataset. The algorithm will highlight its ability to move with the aforementioned consideration towards each individual dynamic agent.

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Cavallin, Kristoffer, and Peter Svensson. "Semi-Autonomous,Teleoperated Search and Rescue Robot." Thesis, Umeå University, Department of Computing Science, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-31928.

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The interest in robots in the urban search and rescue (USAR) field has increased the last two decades. The idea is to let robots move into places where human rescue workers cannot or, due to high personal risks, should not enter.In this thesis project, an application is constructed with the purpose of teleoperating a simple robot. This application contains a user interface that utilizes both autonomous and semi-autonomous functions, such as search, explore and point-and-go behaviours. The purpose of the application is to work with USAR principles in a refined and simplified environment, and thereby increase the understanding for these principles and how they interact with each other. Furthermore, the thesis project reviews the recent and the current status of robots in USAR applications and use of teleoperation and semi-autonomous robots in general. Some conclusions that are drawn towards the end of the thesis are that the use of robots, especially in USAR situations, will continue to increase. As robots and support technology both become more advanced and cheaper by the day, teleoperation and semi-autonomous robots will also be seen in more and more places.

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Wzorek, Mariusz. "Selected Aspects of Navigation and Path Planning in Unmanned Aircraft Systems." Licentiate thesis, Linköpings universitet, UASTECH – Teknologier för autonoma obemannade flygande farkoster, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-71147.

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Unmanned aircraft systems (UASs) are an important future technology with early generations already being used in many areas of application encompassing both military and civilian domains. This thesis proposes a number of integration techniques for combining control-based navigation with more abstract path planning functionality for UASs. These techniques are empirically tested and validated using an RMAX helicopter platform used in the UASTechLab at Linköping University. Although the thesis focuses on helicopter platforms, the techniques are generic in nature and can be used in other robotic systems. At the control level a navigation task is executed by a set of control modes. A framework based on the abstraction of hierarchical concurrent state machines for the design and development of hybrid control systems is presented. The framework is used to specify reactive behaviors and for sequentialisation of control modes. Selected examples of control systems deployed on UASs are presented. Collision-free paths executed at the control level are generated by path planning algorithms.We propose a path replanning framework extending the existing path planners to allow dynamic repair of flight paths when new obstacles or no-fly zones obstructing the current flight path are detected. Additionally, a novel approach to selecting the best path repair strategy based on machine learning technique is presented. A prerequisite for a safe navigation in a real-world environment is an accurate geometrical model. As a step towards building accurate 3D models onboard UASs initial work on the integration of a laser range finder with a helicopter platform is also presented. Combination of the techniques presented provides another step towards building comprehensive and robust navigation systems for future UASs.

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Chen, Fei. "Autonomous Mission Planning for Multi-Terrain Solar-Powered Unmanned Ground Vehicles." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1554387780484243.

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Prusakiewicz, Lukas, and Simon Tönnes. "Comparison of autonomous waypoint navigation methods for an indoor blimp robot." Thesis, KTH, Mekatronik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284458.

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The Unmanned Aerial Vehicle (UAV) has over the last years become an increasingly prevalent technology in several sectors of modern society. Many UAVs are today used in a wide series of applications, from disaster relief to surveillance. A recent initiative by the Swedish Sea Rescue Society (SSRS) aims to implement UAVs in their emergency response. By quickly deploying drones to an area of interest, an assessment can be made, prior to personnel getting there, thus saving time and increasing the likelihood of a successful rescue operation. An aircraft like this, that will travel great distances, have to rely on a navigation system that does not require an operator to continuously see the vehicle. To travel to its goal, or search an area, the operator should be able to define a travel route that the UAV follows, by feeding it a series of waypoints. As an initial step towards that kind of system, this thesis has developed and tested the concept of waypoint navigation on a small and slow airship/blimp, in a simulated indoor environment. Mainly, two commonly used navigation algorithms were tested and compared. One is inspired by a sub-category of machine learning: reinforcement learning (RL), and the other one is based on the rapidly exploring random tree (RRT) algorithm. Four experiments were conducted to compare the two methods in terms of travel distance, average speed, energy efficiency, as well as robustness towards changes in the waypoint configurations. Results show that when the blimp was controlled by the best performing RL-based version, it generally travelled a more optimal (distance-wise) path than the RRT-based method. It also, in most cases, proved to be more robust against changes in the test tracks, and performed more consistently over different waypoint configurations. However, the RRT approach usually resulted in a higher average speed and energy efficiency. Also, the RL algorithm had some trouble navigating tracks where a physical obstacle was present. To sum up, the choice of algorithm depends on which parameters are prioritized by the blimp operator for a certain track. If a high velocity and energy efficiency is desirable, the RRT-based method is recommended. However, if it is important that the blimp travels as short a distance as possible between waypoints, and a higher degree of consistency in its performance is wanted, then the RL-method should be used. Moving forward from this report, toward the future implementation of both methods in rescue operations, it would be reasonable to analyze their performance under more realistic conditions. This can be done using a real indoor airship. Looking at how hardware that do not exceed the payload of the blimp can execute both methods and how the blimp will determine its position and orientation is recommended. It would also be interesting to see how different reward function affect the performance of the blimp. Den obemannade luftfarkosten (UAV) har under de senaste åren blivit en teknik vars användning blivit allt vanligare i flera sektorer av det moderna samhället. Olika sorters UAV robotar associeras idag med en omfattande serie användningsområden, från katastrofhjälp till övervakning. Ett nyligen påbörjat initiativ från svenska sjöräddningssällskapet (SSRS) syftar till att implementera drönare i deras utryckningar. Genom att snabbt sända drönare till platsen i fråga, kan en bedömning göras innan personal kommer dit, vilket sparar tid och ökar sannolikheten för en framgångsrik räddningsaktion. En farkost som denna, som kommer att resa långa sträckor, måste förlita sig på ett navigationssystem som inte kräver att en operatör kontinuerligt ser farkosten. För att resa till sitt mål, eller söka av ett område, bör operatören kunna definiera en resväg som drönaren följer genom att ge den en serie vägpunkter. Som ett inledande steg mot den typen av system har denna uppsats utvecklat och testat begreppet vägpunktsnavigering på ett litet och långsamt luftskepp/blimp, i en simulerad inomhusmiljö. Huvudsakligen testades och jämfördes två vanligt förekommande navigationsalgoritmer. En inspirerad av en underkategori till maskininlärning: förstärkningsinlärning (RL), och den andra baserad på rapidly exploring random tree (RRT) algoritmen. Fyra experiment utfördes för jämföra båda metoderna med avseende på färdsträcka, medelhastighet, energieffektivitet samt robusthet gentemot ändringar i färdpunktskonfigurationerna. Resultaten visar att när blimpen kontrollerades av den bästa RL-baserade versionen åkte den generellt en mer avståndsmässigt optimal väg än när den RRT-baserade metoden användes. I de flesta fallen visade sig även RL-metoden vara mer robust mot förändringar i testbanorna, och presterade mer konsekvent över olika vägpunktskonfigurationer. RRT-metoden resulterade dock vanligtvis i en högre medelhastighet och energieffektivitet. RL-algoritmen hade också problem med att navigera banor där den behövde ta sig runt ett hinder. Sammanfattningsvis beror valet av algoritm på vilka parametrar som prioriteras av blimpoperatören för en viss bana. Om en hög hastighet och energieffektivitet är önskvärd rekommenderas den RRT-baserade metoden. Men om det är viktigt att blimpen reser så kort avstånd som möjligt mellan färdpunkterna, och har en jämnare prestanda, bör RL-metoden användas. För att ta nästa steg, mot en framtida implementering av båda metoder i räddningsoperationer, vore det rimligt att analysera deras prestanda under mer realistiska förhållanden. Detta skulle kunna göras inomhus med ett riktigt luftskepp. Författarna rekommenderar att undersöka om hårdvara som inte överstiger blimpens maxlast kan utföra båda metodernas beräkningar och hur blimpen bestämmer sin position och orientering. Det skulle också vara intressant att se hur olika belöningsfunktioner påverkar blimpens prestanda.

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23

Fayad, Carole. "Development of techniques for global/local path planning of an autonomous mobile robot in dynamic environments." Thesis, University of Nottingham, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368954.

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Diamantopoulos, Anastasios. "A reduced visibility graph approach for motion planning of autonomously guided vehicles." Thesis, University of South Wales, 2001. https://pure.southwales.ac.uk/en/studentthesis/a-reduced-visibility-graph-approach-for-motion-planning-of-autonomously-guided-vehicles(3f368020-0a83-42e5-ba83-b4a4a6257bc2).html.

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This thesis is concerned with the robots' motion planning problem. In particular it is focused on the path planning and motion planning for Autonomously Guided Vehicles (AGVs) in well-structured, two-dimensional static and dynamic environments. Two algorithms are proposed for solving the aforementioned problems. The first algorithm establishes the shortest collision-semi-free path for an AGV from its start point to its goal point, in a two-dimensional static environment populated by simple polygonal obstacles. This algorithm constructs and searches a reduced visibility graph, within the AGV's configuration space, using heuristic information about the problem domain. The second algorithm establishes the time minimal collision-semi-free motion for an AGV, from its start point to is goal point, in a two-dimensional dynamic environment populated by simple polygonal obstacles. This algorithm considers the AGV's spacetime configuration space, thus reducing the dynamic motion planning problem to the static path planning problem. A reduced visibility graph is then constructed and searched using information about the problem domain, in the AGV's space-time configuration space in order to establish the time-minimal motion between the AGV's start and goal configurations. The latter algorithm is extended to solve more complicated instances of the dynamic motion planning problem, where the AGV's environment is populated by obstacles, which change their size as well as their position over time and obstacles, which have piecewise linear motion. The proposed algorithms can be used to efficiently and safely navigate AGVs in well structured environments. For example, for the navigation of an AGV, in industrial environments, where it operates as part of the manufacturing process or in chemical and nuclear plants, where the hostile environment is inaccessible to humans. The main contributions in this thesis are, the systematic study of the V*GRAPH algorithm and identification of its methodic and algorithmic deficiencies; recommendation of corrections and further improvements on the V* GRAPH algorithm, which in turn lead to the proposition of the V*MECHA algorithm for robot path planning; proposition of the D*MECHA algorithm for motion planning in dynamic environments; extension to the D*MECHA algorithm to solve more complicated instances of the dynamic robot motion planning problem; discussion of formal proofs of the proposed algorithms' correctness and optimality and critical comparisons with existing similar algorithms for solving the motion planning problem.

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Nilsson, Per Johan Fredrik. "Planning semi-autonomous drone photo missions in Google Earth." Thesis, Mittuniversitetet, Avdelningen för data- och systemvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-31473.

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This report covers an investigation of the methods and algorithms required to plan and perform semi-autonomous photo missions on Apple iPad devices using data exported from Google Earth. Flight time was to be minimized, taking wind velocity and aircraft performance into account. Google Earth was used both to define what photos to take, and to define the allowable mission area for the aircraft. A benchmark mission was created containing 30 photo operations in a 250 by 500 m area containing several no-fly-areas. The report demonstrates that photos taken in Google Earth can be reproduced in reality with good visual resemblance. High quality paths between all possible photo operation pairs in the benchmark mission could be found in seconds using the Theta* algorithm in a 3D grid representation with six-edge connectivity (Up, Down, North, South, East, West). Smoothing the path in a post-processing step was shown to further increase the quality of the path at a very low computational cost. An optimal route between the operations in the benchmark mission, using the paths found by Theta*, could be found in less than half a minute using a Branch-and-Bound algorithm. It was however also found that prematurely terminating the algorithm after five seconds yielded a route that was close enough to optimal not to warrant running the algorithm to completion.

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Cheng, Yongqiang. "Wireless mosaic eyes based robot path planning and control : autonomous robot navigation using environment intelligence with distributed vision sensors." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/4421.

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As an attempt to steer away from developing an autonomous robot with complex centralised intelligence, this thesis proposes an intelligent environment infrastructure where intelligences are distributed in the environment through collaborative vision sensors mounted in a physical architecture, forming a wireless sensor network, to enable the navigation of unintelligent robots within that physical architecture. The aim is to avoid the bottleneck of centralised robot intelligence that hinders the application and exploitation of autonomous robot. A bio-mimetic snake algorithm is proposed to coordinate the distributed vision sensors for the generation of a collision free Reference-snake (R-snake) path during the path planning process. By following the R-snake path, a novel Accompanied snake (A-snake) method that complies with the robot's nonholonomic constraints for trajectory generation and motion control is introduced to generate real time robot motion commands to navigate the robot from its current position to the target position. A rolling window optimisation mechanism subject to control input saturation constraints is carried out for time-optimal control along the A-snake. A comprehensive simulation software and a practical distributed intelligent environment with vision sensors mounted on a building ceiling are developed. All the algorithms proposed in this thesis are first verified by the simulation and then implemented in the practical intelligent environment. A model car with less on-board intelligence is successfully controlled by the distributed vision sensors and demonstrated superior mobility.

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Chen, Qi. "Studies in autonomous ground vehicle control systems structure and algorithms /." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1165959992.

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Ezequiel, Carlos Favis. "Real-Time Map Manipulation for Mobile Robot Navigation." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4481.

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Mobile robots are gaining increased autonomy due to advances in sensor and computing technology. In their current form however, robots still lack algorithms for rapid perception of objects in a cluttered environment and can benefit from the assistance of a human operator. Further, fully autonomous systems will continue to be computationally expensive and costly for quite some time. Humans can visually assess objects and determine whether a certain path is traversable, but need not be involved in the low-level steering around any detected obstacles as is necessary in remote-controlled systems. If only used for rapid perception tasks, the operator could potentially assist several mobile robots performing various tasks such as exploration, surveillance, industrial work and search and rescue operations. There is a need to develop better human-robot interaction paradigms that would allow the human operator to effectively control and manage one or more mobile robots. This paper proposes a method of enhancing user effectiveness in controlling multiple mobile robots through real-time map manipulation. An interface is created that would allow a human operator to add virtual obstacles to the map that represents areas that the robot should avoid. A video camera is connected to the robot that would allow a human user to view the robot's environment. The combination of real-time map editing and live video streaming enables the robot to take advantage of human vision, which is still more effective at general object identification than current computer vision technology. Experimental results show that the robot is able to plan a faster path around an obstacle when the user marks the obstacle on the map, as opposed to allowing the robot to navigate on its own around an unmapped obstacle. Tests conducted on multiple users suggest that the accuracy in placing obstacles on the map decreases with increasing distance of the viewing apparatus from the obstacle. Despite this, the user can take advantage of landmarks found in the video and in the map in order to determine an obstacle's position on the map.

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Elias, Ricardo. "A VIRTUAL REALITY VISUALIZATION OFAN ANALYTICAL SOLUTION TOMOBILE ROBOT TRAJECTORY GENERATIONIN THE PRESENCE OF MOVING OBSTACLES." Master's thesis, University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2438.

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Virtual visualization of mobile robot analytical trajectories while avoiding moving obstacles is presented in this thesis as a very helpful technique to properly display and communicate simulation results. Analytical solutions to the path planning problem of mobile robots in the presence of obstacles and a dynamically changing environment have been presented in the current robotics and controls literature. These techniques have been demonstrated using two-dimensional graphical representation of simulation results. In this thesis, the analytical solution published by Dr. Zhihua Qu in December 2004 is used and simulated using a virtual visualization tool called VRML. M.S.E.E. School of Electrical Engineering and Computer Science Engineering and Computer Science Electrical Engineering MSEE

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Bays, Matthew Jason. "Stochastic Motion Planning for Applications in Subsea Survey and Area Protection." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/26763.

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This dissertation addresses high-level path planning and cooperative control for autonomous vehicles. The objective of our work is to closely and rigorously incorporate classication and detection performance into path planning algorithms, which is not addressed with typical approaches found in literature. We present novel path planning algorithms for two different applications in which autonomous vehicles are tasked with engaging targets within a stochastic environment. In the first application an autonomous underwater vehicle (AUV) must reacquire and identify clusters of discrete underwater objects. Our planning algorithm ensures that mission objectives are met with a desired probability of success. The utility of our approach is verified through field trials. In the second application, a team of vehicles must intercept mobile targets before the targets enter a specified area. We provide a formal framework for solving the second problem by jointly minimizing a cost function utilizing Bayes risk. Ph. D.

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Girbés, Juan Vicent. "Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving)." Doctoral thesis, Universitat Politècnica de València, 2016. http://hdl.handle.net/10251/65072.

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[EN] Nowadays, there are many electronic products that incorporate elements and features coming from the research in the field of mobile robotics. For instance, the well-known vacuum cleaning robot Roomba by iRobot, which belongs to the field of service robotics, one of the most active within the sector. There are also numerous autonomous robotic systems in industrial warehouses and plants. It is the case of Autonomous Guided Vehicles (AGVs), which are able to drive completely autonomously in very structured environments. Apart from industry and consumer electronics, within the automotive field there are some devices that give intelligence to the vehicle, derived in most cases from advances in mobile robotics. In fact, more and more often vehicles incorporate Advanced Driver Assistance Systems (ADAS), such as navigation control with automatic speed regulation, lane change and overtaking assistant, automatic parking or collision warning, among other features. However, despite all the advances there are some problems that remain unresolved and can be improved. Collisions and rollovers stand out among the most common accidents of vehicles with manual or autonomous driving. In fact, it is almost impossible to guarantee driving without accidents in unstructured environments where vehicles share the space with other moving agents, such as other vehicles and pedestrians. That is why searching for techniques to improve safety in intelligent vehicles, either autonomous or manual-assisted driving, is still a trending topic within the robotics community. This thesis focuses on the design of tools and techniques for planning and control of intelligent vehicles in order to improve safety and comfort. The dissertation is divided into two parts, the first one on autonomous driving and the second one on manual-assisted driving. The main link between them is the use of clothoids as mathematical formulation for both trajectory generation and collision detection. Among the problems solved the following stand out: obstacle avoidance, rollover avoidance and advanced driver assistance to avoid collisions with pedestrians. [ES] En la actualidad se comercializan infinidad de productos de electrónica de consumo que incorporan elementos y características procedentes de avances en el sector de la robótica móvil. Por ejemplo, el conocido robot aspirador Roomba de la empresa iRobot, el cual pertenece al campo de la robótica de servicio, uno de los más activos en el sector. También hay numerosos sistemas robóticos autónomos en almacenes y plantas industriales. Es el caso de los vehículos autoguiados (AGVs), capaces de conducir de forma totalmente autónoma en entornos muy estructurados. Además de en la industria y en electrónica de consumo, dentro del campo de la automoción también existen dispositivos que dotan de cierta inteligencia al vehículo, derivados la mayoría de las veces de avances en robótica móvil. De hecho, cada vez con mayor frecuencia los vehículos incorporan sistemas avanzados de asistencia al conductor (ADAS por sus siglas en inglés), tales como control de navegación con regulación automática de velocidad, asistente de cambio de carril y adelantamiento, aparcamiento automático o aviso de colisión, entre otras prestaciones. No obstante, pese a todos los avances siguen existiendo problemas sin resolver y que pueden mejorarse. La colisión y el vuelco destacan entre los accidentes más comunes en vehículos con conducción tanto manual como autónoma. De hecho, la dificultad de conducir en entornos desestructurados compartiendo el espacio con otros agentes móviles, tales como coches o personas, hace casi imposible garantizar la conducción sin accidentes. Es por ello que la búsqueda de técnicas para mejorar la seguridad en vehículos inteligentes, ya sean de conducción autónoma o manual asistida, es un tema que siempre está en auge en la comunidad robótica. La presente tesis se centra en el diseño de herramientas y técnicas de planificación y control de vehículos inteligentes, para la mejora de la seguridad y el confort. La disertación se ha dividido en dos partes, la primera sobre conducción autónoma y la segunda sobre conducción manual asistida. El principal nexo de unión es el uso de clotoides como elemento de generación de trayectorias y detección de colisiones. Entre los problemas que se resuelven destacan la evitación de obstáculos, la evitación de vuelcos y la asistencia avanzada al conductor para evitar colisiones con peatones. [CAT] En l'actualitat es comercialitzen infinitat de productes d'electrònica de consum que incorporen elements i característiques procedents d'avanços en el sector de la robòtica mòbil. Per exemple, el conegut robot aspirador Roomba de l'empresa iRobot, el qual pertany al camp de la robòtica de servici, un dels més actius en el sector. També hi ha nombrosos sistemes robòtics autònoms en magatzems i plantes industrials. És el cas dels vehicles autoguiats (AGVs), els quals són capaços de conduir de forma totalment autònoma en entorns molt estructurats. A més de en la indústria i en l'electrònica de consum, dins el camp de l'automoció també existeixen dispositius que doten al vehicle de certa intel·ligència, la majoria de les vegades derivats d'avanços en robòtica mòbil. De fet, cada vegada amb més freqüència els vehicles incorporen sistemes avançats d'assistència al conductor (ADAS per les sigles en anglés), com ara control de navegació amb regulació automàtica de velocitat, assistent de canvi de carril i avançament, aparcament automàtic o avís de col·lisió, entre altres prestacions. No obstant això, malgrat tots els avanços segueixen existint problemes sense resoldre i que poden millorar-se. La col·lisió i la bolcada destaquen entre els accidents més comuns en vehicles amb conducció tant manual com autònoma. De fet, la dificultat de conduir en entorns desestructurats compartint l'espai amb altres agents mòbils, tals com cotxes o persones, fa quasi impossible garantitzar la conducció sense accidents. És per això que la recerca de tècniques per millorar la seguretat en vehicles intel·ligents, ja siguen de conducció autònoma o manual assistida, és un tema que sempre està en auge a la comunitat robòtica. La present tesi es centra en el disseny d'eines i tècniques de planificació i control de vehicles intel·ligents, per a la millora de la seguretat i el confort. La dissertació s'ha dividit en dues parts, la primera sobre conducció autònoma i la segona sobre conducció manual assistida. El principal nexe d'unió és l'ús de clotoides com a element de generació de trajectòries i detecció de col·lisions. Entre els problemes que es resolen destaquen l'evitació d'obstacles, l'evitació de bolcades i l'assistència avançada al conductor per evitar col·lisions amb vianants. Girbés Juan, V. (2016). Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving) [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/65072 TESIS

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32

Muralidharan, Aravind. "Sonar Based Navigation: Follow the Leader for Bearcat III." Cincinnati, Ohio : University of Cincinnati, 2001. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=ucin998320900.

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33

Schmitz, Austin. "Row crop navigation by autonomous ground vehicle for crop scouting." Thesis, Kansas State University, 2017. http://hdl.handle.net/2097/36237.

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Master of Science Department of Biological & Agricultural Engineering Daniel Flippo Robotic vehicles have the potential to play a key role in the future of agriculture. For this to happen designs that are cost effective, robust, and easy to use will be necessary. Robotic vehicles that can pest scout, monitor crop health, and potentially plant and harvest crops will provide new ways to increase production within agriculture. At this time, the use of robotic vehicles to plant and harvest crops poses many challenges including complexity and power consumption. The incorporation of small robotic vehicles for monitoring and scouting fields has the potential to allow for easier integration of robotic systems into current farming practices as the technology continues to develop. Benefits of using unmanned ground vehicles (UGVs) for crop scouting include higher resolution and real time mapping, measuring, and monitoring of pest location density, crop nutrient levels, and soil moisture levels. The focus of this research is the ability of a UGV to scout pest populations and pest patterns to complement existing scouting technology used on UAVs to capture information about nutrient and water levels. There are many challenges to integrating UGVs in conventionally planted fields of row crops including intra-row and inter-row maneuvering. For intra-row maneuvering; i.e. between two rows of corn, cost effective sensors will be needed to keep the UGV between straight rows, to follow contoured rows, and avoid local objects. Inter-row maneuvering involves navigating from long straight rows to the headlands by moving through the space between two plants in a row. Oftentimes headland rows are perpendicular to the row that the UGV is within and if the crop is corn, the spacing between plants can be as narrow as 5”. A vehicle design that minimizes or eliminates crop damage when inter-row maneuvering occurs will be very beneficial and allow for earlier integration of robotic crop scouting into conventional farming practices. Using three fixed HC-SR04 ultrasonic sensors with LabVIEW programming proved to be a cost effective, simple, solution for intra-row maneuvering of an unmanned ground vehicle through a simulated corn row. Inter-row maneuvering was accomplished by designing a transformable tracked vehicle with the two configurations of the tracks being parallel and linear. The robotic vehicle operates with tracks parallel to each other and skid steering being the method of control for traveling between rows of corn. When the robotic vehicle needs to move through narrow spaces or from one row to the next, two motors rotate the frame of the tracks to a linear configuration where one track follows the other track. In the linear configuration the vehicle has a width of 5 inches which allows it to move between corn plants in high population fields for minimally invasive maneuvers. Fleets of robotic vehicles will be required to perform scouting operations on large fields. Some robotic vehicle operations will require coordination between machines to complete the tasks assigned. Simulation of the path planning for coordination of multiple machines was studied within the context of a non-stationary traveling salesman problem to determine optimal path plans.

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Sinyukov, Dmitry Aleksandrovich. "Semi-autonomous robotic wheelchair controlled with low throughput human- machine interfaces." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-dissertations/242.

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For a wide range of people with limited upper- and lower-body mobility, interaction with robots remains a challenging problem. Due to various health conditions, they are often unable to use standard joystick interface, most of wheelchairs are equipped with. To accommodate this audience, a number of alternative human-machine interfaces have been designed, such as single switch, sip-and-puff, brain-computer interfaces. They are known as low throughput interfaces referring to the amount of information that an operator can pass into the machine. Using them to control a wheelchair poses a number of challenges. This thesis makes several contributions towards the design of robotic wheelchairs controlled via low throughput human-machine interfaces: (1) To improve wheelchair motion control, an adaptive controller with online parameter estimation is developed for a differentially driven wheelchair. (2) Steering control scheme is designed that provides a unified framework integrating different types of low throughput human-machine interfaces with an obstacle avoidance mechanism. (3) A novel approach to the design of control systems with low throughput human-machine interfaces has been proposed. Based on the approach, position control scheme for a holonomic robot that aims to probabilistically minimize time to destination is developed and tested in simulation. The scheme is adopted for a real differentially driven wheelchair. In contrast to other methods, the proposed scheme allows to use prior information about the user habits, but does not restrict navigation to a set of pre-defined points, and parallelizes the inference and motion reducing the navigation time. (4) To enable the real time operation of the position control, a high-performance algorithm for single-source any-angle path planning on a grid has been developed. By abandoning the graph model and introducing discrete geometric primitives to represent the propagating wave front, we were able to design a planning algorithm that uses only integer addition and bit shifting. Experiments revealed a significant performance advantage. Several modifications, including optimal and multithreaded implementations, are also presented.

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Coelho, Fabrício de Oliveira. "Missões autônomas em robôs móveis com tração diferencial: planejamento de caminhos, localização e mapeamento." Universidade Federal de Juiz de Fora (UFJF), 2018. https://repositorio.ufjf.br/jspui/handle/ufjf/6497.

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Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-03-27T13:16:05Z No. of bitstreams: 1 fabriciodeoliveiracoelho.pdf: 19075776 bytes, checksum: 5f9c07d95c6d348d64825d66fda1c6f3 (MD5) Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-03-27T13:40:24Z (GMT) No. of bitstreams: 1 fabriciodeoliveiracoelho.pdf: 19075776 bytes, checksum: 5f9c07d95c6d348d64825d66fda1c6f3 (MD5) Made available in DSpace on 2018-03-27T13:40:24Z (GMT). No. of bitstreams: 1 fabriciodeoliveiracoelho.pdf: 19075776 bytes, checksum: 5f9c07d95c6d348d64825d66fda1c6f3 (MD5) Previous issue date: 2018-02-08 CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Esse trabalho apresenta uma metodologia para a concepção de missões autônomas utilizando robôs móveis com tração diferencial em ambientes internos. As missões consistem em deslocar o robô até uma posição objetivo partindo de uma pose inicial. Para que as missões ocorram com sucesso, são implementados algoritmos de localização e planejamento de caminhos. Para localização, foi utilizado Filtro de Kalman Estendido (do inglês, Extended Kalman Filter EKF) para fundir a odometria com visão computacional. A visão é responsável por encontrar marcadores artificiais conhecidos como Ar codes que são alocados no ambiente. O planejamento é caracterizado por uma forma híbrida que corresponde a união de um método deliberativo e reativo. No Planejamento deliberativo, foi proposto e utilizado o método Direct-DRRT* cuja base é oriunda do RRT (Rapidly Exploring Random Tree). Além do RRT, esse planejador também apresenta características de dois outros métodos já presentes na literatura: RRT* e DRRT. O planejador deliberativo enviará para o reativo um conjunto de sub-objetivos que conecta a posição em que o robô se encontra até o objetivo final. O planejamento reativo é aplicado durante a missão e é o responsável pelo desvio de obstáculos dinâmicos que não foram mapeados. No Reativo, é utilizado o método dos Campos Potenciais Artificiais (CPA), que também se comporta como o controlador do robô durante a navegação. Para encontrar os obstáculos, utilizou-se o sensor de profundidade Asus Xtion, pois, a partir das imagens geradas por esse sensor, é possível encontrar as distâncias que os bloqueios se encontram. As informações desse sensor também será de grande valia na atualização do mapa. O sistema é integrado através da framework ROS (Robot Operating System). Todos os algoritmos foram implementados por meio da linguagem de programação Python. Os resultados do trabalho foram apresentados por meio do simulador Gazebo e testes práticos a partir da plataforma P3DX. Foram analisados o comportamento do robô em alguns problemas que podem ocorrer durante a navegação, como o sequestro e aparecimento mínimos locais. Ao final desse trabalho, apresentou-se a melhoria nos resultados do planejador de caminhos Direct-DRRT*, onde foi possível constatar a queda no tempo para obter um caminho, a quantidade de iterações, de nós e do comprimento do caminho em comparação aos outros métodos. No que tange à localização, essa dissertação obteve significativas melhoras comparado com o método que utiliza somente a odometria. Além desse resultado, esse trabalho também obteve sucesso em apresentar uma solução para a implementação de missões autônomas. This work presents a design methodology for autonomous missions using mobile robots with differential traction in indoor environments. The missions consist of moving the robot to a goal position starting from an initial pose. For missions success, it is necessary to implement localization and path planning algorithms. For localization, Extended Kalman Filters (EKF) used to fuse odometry with computational vision. The view is responsible for finding artificial markers known as Ar codes that are presented in the environment. The planning is characterized by a hybrid form that corresponds to the union of a deliberative and reactive methods. In the Deliberative Planning, the Direct-DRRT * method, whose base is derived from the Rapidly Exploring Random Tree (RRT), is proposed and used. In addition to the RRT, this planner also presents characteristics of two other methods already presented in the literature, i.e. RRT * and DRRT. The deliberative planner sends to the reactive a set of sub-objectives that connects the initial position to the final goal. Reactive planning is applied during the mission and it is responsible for the dynamic obstacles avoidance that have not been mapped. In the reactive, the Artificial Potential Fields (APF) method is used, which also behaves as the robot controller during navigation. To find the obstacles, we use the sensor Asus Xtion, due to the possibility to find the distances that the locks are in the images generated by this sensor. All the algorithms were implemented through the programming language Python. The results of the work were presented through the simulator Gazebo and practical tests using the P3DX platform. We analyzed the robot behavior in some problems that may occur during navigation, such as kidnapped and local minimum appearance. At the end, the improvement in the results of the Direct-DRRT * path planner is also presented. It is possible to verify the decrease in the time to obtain a path, the number of iterations of nodes and the path length in comparison to other methods. Regarding the location, this dissertation has obtained significant improvements when compared to the methods that use only odometry. Besides, the work was also successful in presenting a solution for the autonomous missions implementation.

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Sanches, Rodrigo Marcon. "Desenvolvimento de um sistema de planejamento de trajetória para veículos autônomos agrícolas." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/18/18149/tde-29112012-211414/.

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O objetivo deste trabalho é desenvolver um sistema de navegação global para que veículos agrícolas autônomos possam executar missões em campos de cultivo através de um sistema de planejamento de trajetórias. Missões podem ser entendidas como sendo tarefas (p.ex.: de monitoramento, coleta de amostras, etc.) através de pequenas rotas que os veículos devem seguir ao longo de seus trabalhos diários, percorrendo a menor distância possível entre os pontos de origem e destino. O planejamento de trajetória foi dividido em etapas para facilitar o entendimento de cada uma delas. O mapeamento apresentado neste trabalho foi feito em regiões de cultivo de café nos estados de São Paulo e Minas Gerais. Os pontos do mapa foram amostrados utilizando um módulo receptor de sinal GPS (Global Positioning System) ao longo dos caminhos onde é possível a passagem do veículo dentro da plantação. Uma etapa importante para o sucesso deste sistema é a etapa de pré-processamento dos dados. Nesta etapa são inseridas as relações entre os pontos do mapeamento da área. As missões foram pré-definidas de modo a testar o cálculo do caminho de custo mínimo que é realizado através do algoritmo de Dijkstra. A cada ponto da rota é fornecido o ângulo de direção com o qual o veículo deve estar em relação ao Norte geográfico. De acordo com a mudança pretendida do ângulo de direção é proposta uma suavização nesta mudança através da alteração do percurso para um arco de circunferência. Neste caso, o raio de giro é informado. A última etapa consiste em fornecer a velocidade máxima de deslocamento do veículo em função da mudança de direção e velocidade angular máxima do centro de massa do veículo. O sistema proposto neste trabalho foi capaz de determinar o caminho com a menor distância entre dois pontos do mapeamento (coordenadas geográficas) e o calcular da distância entre os pontos. Embora a fórmula utilizada para calcular a distância entre duas coordenadas geográficas considerar o formato da Terra como sendo uma esfera, isto não gerou erro significativo para a aplicação proposta. A suavização proposta possibilitou, em alguns pontos, o aumento da velocidade de deslocamento por fazer a mudança do ângulo de direção de forma menos abrupta. The objective of this work is to develop a global navigation system for autonomous agricultural vehicles can perform missions in crop fields through a system of path planning. Missions can be understood as tasks (eg monitoring, sampling, etc.). Through small routes that vehicles must follow throughout their daily jobs, traveling the shortest possible distance between the points of origin and destination. The path planning was divided into steps to make it easy to understand each one. The mapping presented in this work was done in coffee-growing regions in the state of São Paulo and Minas Gerais. The map points have been sampled using a GPS receiver module along the path where it is possible to move the vehicle within the plantation. An important step for the success of this system is the data pre-processing step. In this step are inserted the relations between the points of the mapping. The missions are predefined in order to test if the calculation of the minimum cost path made by Dijkstra algorithm is correct. At each point of the route is given the vehicle heading angle (vehicle position towards the geographic North). According to the intended change of the heading angle is proposed a smoothing method to smooth this change by changing the route to an arc. In this case, the turning radius is reported. The last step is to provide the maximum speed of the vehicle due to the change of direction and maximum angular speed of the center of mass. The system proposed in this paper was able to determine the path with the shortest distance between two points of the mapping (geographic coordinates) and calculate the distance between these points. Although the formula used to calculate the distance between two geographical coordinates consider the shape of the Earth as a sphere, this did not generate significant errors for the proposed application. The proposed smoothing allowed, in some cases, to increase the vehicle speed by making the change of heading angle less abrupt.

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Sant\'Ana, Felipe Taha. "Estimação de probabilidade de colisão com obstáculos móveis para navegação autônoma." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-04082015-113151/.

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Na área de robótica móvel autônoma é importante que o robô siga uma trajetória livre de obstáculos. Estes podem ser desde obstáculos estáticos, como paredes e cadeiras em um ambiente interno, ou mesmo obstáculos móveis, como pessoas caminhando na calçada e carros passando pela rua, quando consideramos ambientes externos. No caso de um ambiente estático, o problema pode ser resolvido planejando uma trajetória livre de colisões, sendo que não é necessário um replanejamento se todos os obstáculos estáticos foram considerados. Para ambientes onde os obstáculos estão em constante movimento, é necessário um constante replanejamento da trajetória para que se evite colisões. Alternativamente, pode ser verificada a possibilidade de se manter na rota planejada, alterando apenas a velocidade de cruzeiro do robô para que este desvie dos obstáculos móveis. Este trabalho propõe uma metodologia para calcular uma velocidade de cruzeiro para o robô de forma a minimizar a probabilidade de colisão com os obstáculos detectados pelos seus sensores. A escolha da variação de velocidade para o robô considera a sua velocidade atual, e as velocidades estimadas para os obstáculos. A metodologia para resolução deste problema é apresentada considerando incertezas na posição do robô e obstáculos. São apresentados resultados de simulação que exemplificam a aplicação da metodologia. Following a free path is an important issue in the area of autonomous mobile robotics. The obstacles can be anything from walls and chairs in an indoor environment, or they can also be people walking on the sidewalk and cars moving through the street. In the case of a static environment, the problem can be solved by planning a path free from collisions, thus it is not essential another path planning as all static obstacles were considered. For an environment were the obstacles are constantly moving, it is necessary an unceasing path replanning to avoid possible collisions. Alternatively, keeping the robot on the previously calculated path can be verified modifying the robot\'s traffic velocity to avoid moving obstacles. Our proposal is to calculate a velocity for the robot which minimizes its collision probability with moving obstacles detected by its sensors. Varying the robot\'s velocity takes into account its current velocity and the estimated velocities of obstacles. The methodology for solving this problem is presented regarding uncertainties in robots and obstacles\' positions. Results from simulations that exemplifies an application for the methodology are presented.

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Sert, Hugues. "De l’utilisation de l’algèbre différentielle pour la localisation et la navigation de robots mobiles autonomes." Thesis, Ecole centrale de Lille, 2013. http://www.theses.fr/2013ECLI0002/document.

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Ce travail étudie l'apport de l'algèbre différentielle à deux problématiques principales de la robotique mobile à roues, la localisation et la navigation. La première problématique consiste à être capable de dire où le robot se situe dans son environnement. Nous supposons ici que nous possédons un certain nombre de points d'intérêt de l'espace dont les coordonnées dans cette espace sont connues. En fonction du nombre de points d'intérêt, il est possible ou non de localiser le robot. Cette notion de localisabilité est définie et étudiée dans le cadre algébrique. Nous montrons que ce cadre d'étude est plus intéressant que le cadre géométrique en ce sens que non seulement il permet l'étude de la localisabilité mais en plus il permet de construire des estimateurs d'états permettant de reconstruire la posture du robot. Cette étude est effectuée dans cinq cas d'études pour quatre des cinq classes de robots mobiles à roues. La deuxième problématique étudiée est celle de la navigation d'une flottille décentralisée de robots dans un environnement complexe. Ce travail présente une architecture pouvant être utilisée dans une large classe de problème et bénéficiant des avantages des approches discrètes et des approches continues. En effet, à haut niveau, un bloc stratégie spécifie l'objectif, les contraintes et leurs paramètres ainsi que la fonction coût utilisée, à bas niveau, une trajectoire est calculée afin de minimiser la fonction coût en respectant l'objectif et les contraintes du problème. Cette minimisation est faite sur un horizon glissant de manière à pouvoir prendre en compte des modifications de l'environnement ou de la mission en cours de navigation This work investigates the contribution of differential algebra to two main issues of wheel mobile robotics, localization and navigation. The first issue is to be able to tell where the robot is in its environment. We assume that we have a number of landmarks in space whose coordinates are known in this area. Depending on the number of landmarks, it is possible or not to localize the robot. This notion of localizability is defined and studied in the algebraic framework. We show that this framework is more interesting than the geometric framework in the sense that it not only allows the study of localizability, but it also allows us to construct estimators states to reconstruct the posture of the robot. This study was conducted in five cases study for four of the five classes of wheeled mobile robots. The second problem studied is that of a robot decentralized swarm navigation in a complex environment. This work presents an architecture that can be used in a wide class of problems and enjoying the benefits of discrete approaches and continuous approaches. Indeed, high-level block strategy specifies the goal, constraints and parameters as well as the cost function, a low-level block is used to compute a trajectory that minimize the cost function in accordance with the objective and the problem constraints. This minimization is done on a sliding window so it is possible to take changes in the environment or mission during navigation into account

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Rusu, Alexandru. "Planification de chemin et navigation autonome pour un rover d’exploration planétaire." Thesis, Toulouse, ISAE, 2014. http://www.theses.fr/2014ESAE0049/document.

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Dans le cadre du programme ExoMars, l’ESA va déployer un rover sur Mars dont la mission sera de réaliser des prélèvements d’échantillons par forage souterrain et les analyser à l’aide des instruments scientifiques embarqués. Pour atteindre en toute sécurité les différents points d’intérêt où seront effectués ces prélèvements, le rover devra être capable de parcourir plus de 70 mètres par sol (jour martien) tout en respectant les limitations des communications interplanétaires. Les performances des algorithmes de navigation autonome embarqués impacteront directement la réussite scientifique de cette mission. Le premier objectif de cette thèse est d’améliorer les performances de l’architecture de planification de chemin local itératif proposée par le CNES. Tout d’abord, l’utilisation d’un planificateur incrémental de chemin local ”Fringe Retrieving A∗” permettant de réduire la charge de calcul est proposée. Il est complété par l’introduction de tas binaires dans les structures de gestion de la liste de priorité du planificateur de chemin.Ensuite, les manœuvres de rotation sur place pendant l’exécution des trajectoires sont réduites à l’aide d’un planificateur de chemins non-holonomes. Ce planificateur utilise un ensemble de chemins pré-calculés en tenant compte des capacités de braquage du rover. Le second axe de recherche concerne la planification de chemin global d’un rover d’exploration planétaire. Dans un premier temps, la contrainte de mémoire embarquée est détendue et une étude statistique évalue la pertinence d’un planificateur de chemin de type D∗ lite. Dans un deuxième temps, une nouvelle représentation multi-résolution de la carte de navigation est proposée pour stocker de plus grandes zones explorées par le rover sans augmenter l’utilisation de la mémoire embarquée. Cette représentation est utilisée par la suite par un planificateur de chemin global qui réduit automatiquement la charge de calcul en adaptant le sens de recherche en fonction de la forme et de la distribution des obstacles dans l’espace de navigation ESA’s ExoMars mission will deploy a 300kg class rover on Mars, which will serveas a mobile platform for the onboard scientific instruments to reach safely desired locations where subsurface drilling and scientific measurements are scheduled. Due to the limited inter-planetary communication constraints, full autonomous on board navigation capabilities are crucial as the rover has to drive over 70 meters per sol(Martian day) to reach designated scientific sites. The core of the navigation softwareto be deployed on the ExoMars rover uses as baseline the autonomous navigation architecture developed by CNES during the last 20 years. Such algorithms are designed to meet the mission-specific constraints imposed by the available spatial technology such as energy consumption, memory, computation power and time costs.The first objective of this thesis is to improve the performance of the successive localpath planning architecture proposed by CNES. First, the use of an increment allocal path planner, Fringe Retrieving A∗, is proposed to reduce the path planning computation load. This is complemented by the introduction of binary heaps in the management structures of the path planner. In-place-turn maneuvers during trajectory execution are further reduced by using a state lattice path planner which encodes the steering capabilities of the rover.The second research direction concerns global path planning capabilities for roboticplanetary exploration. First the onboard memory constraints are relaxed and a studyevaluating the use of a global D∗ lite path planner is performed. Second, a novel multi-resolution representation of the navigation map which covers larger areas atno memory cost increase is proposed. It is further used by a global path planner which automatically reduces the computational load by selecting its search direction based on obstacle shapes and distribution in the navigation space

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Megda, Poliane Torres. "Detecção e classificação de obstáculos aplicados ao planejamento de trajetórias para veículos de passeio em ambiente urbano." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/18/18149/tde-24072013-111120/.

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Todos os dias a quantidade de veículos nas estradas em todo o mundo está aumentando. Este crescimento combinado com a negligência dos motoristas e alguns fatores externos, tais como estradas mal conservadas e condições climáticas adversas resultaram em um enorme aumento na quantidade de acidentes e, conseqüentemente, de mortes. Atualmente muitos grupos de pesquisa e empresas automotivas estão desenvolvendo e adaptando tecnologias que podem ser incorporadas nos veículos para reduzir esses números. Um exemplo interessante dessas tecnologias é a detecção e classificação de obstáculos móveis (veículos, pessoas, etc.) em ambientes urbanos. Este trabalho apresenta o desenvolvimento de algoritmos para identificação, rastreamento e previsão de obstáculos móveis, determinação de direções proibidas para tráfego do veículo e cálculo de trajetórias livres de colisões. Para isso, foram utilizados dados do sistema de medidas de distância, SICK LMS 291-S05, para monitorar o ambiente a frente do veículo de teste (um automóvel de passeio modificado). Com base nesses dados foi realizado um tratamento computacional através da técnica de Trackers para classificar todos os obstáculos detectados em duas classes principais: os obstáculos estáticos e móveis. Uma vez identificado o obstáculo, este será acompanhado mesmo no caso em que saia do campo de visão do sensor. Após a classificação dos obstáculos presentes no ambiente, suas posições são analisadas e direções proibidas para tráfego são determinadas peloalgoritmo Velocity Obstacle Approach. Finalmente é aplicada a técnica de cálculo de trajetórias E* que gera um caminho suave e livre de colisões. No caso de algum obstáculo obstruir ou gerar risco de colisão com o caminho gerado é possível recalcular a rota sem que o mapa do ambiente seja novamente completamente analisado. Os resultados obtidos demonstraram a aplicabilidade da metodologia utilizada. O algoritmo de Trackers detectou pedestres e veículos e determinou suas características dinâmicas. O algoritmo Velocity Obstacle Approach conseguiu acompanhar os obstáculos e foi capaz de determinar as direções proibidas e, finalmente, o algoritmo E* foi capaz de gerar trajetórias livre de obstáculos em ambientes desconhecidos. Every day the number of vehicles on the roads around the world is increasing. This growth combined with the negligence of drivers and some external factors such as poorly maintained roads and adverse weather conditions resulted in a huge increase in the number of accidents and hence casualties. Currently many research groups and automotive companies are developing and adapting technologies that can be incorporated into vehicles to reduce these numbers. An interesting example of these technologies is the detection and classification of moving obstacles (vehicles, people, etc.) in urban environments. This dissertation presents the development of algorithms which main objective are identify, track and predict moving obstacles, determine prohibited directions of traffic and calculate collision free trajectories. In order to accomplish with such task, data from the laser sensor SICK LMS 291-S05 later treated using computational resources such as the Trackers technique was used to monitor the environment ahead of the test vehicle (a modified passenger car). The Trackers technique was used to classify all the hurdles identified in two main classes: static and mobile obstacles. Once the obstacle was identified, this still been followed even if they leave the field of vision sensor. After classification of obstacles in the environment, their positions are analyzed and prohibited for traffic directions are determined by the algorithm Velocity Obstacle Approach. Finally the technique is applied to calculate trajectories of E* that generates a smooth path and free of collisions. If any obstacle block, or create a risk of collision through the generated path, the trajectory can be recalculated without the need to fully re-analyze de environment map. The results demonstrated the applicability of the methodology used. The Trackers algorithm has detected pedestrians and vehicles determining their dynamic characteristics. The algorithm Velocity Obstacle Approach keep up with the obstacles and was able to determine the prohibited directions and, finally, E* the algorithm was able to generate obstacle-free paths in unknown environments.

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Ferreira, Giordano Bruno Santos. "Modelos baseados em autômatos celulares para o planejamento de caminhos em robôs autônomos." Universidade Federal de Uberlândia, 2014. https://repositorio.ufu.br/handle/123456789/12573.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico Considering path planning problem for autonomous robots, the objective is to find a list of steps to be applied to obtain a path between the initial point and the goal. This work aims the investigation and implementation of cellular automata (CA) based models to path-planning. In an initial phase, a comparative study was conducted among the cellular automata-based methods to path-planning published in the literature. Subsequently, two published works were chosen to be implemented in simulation environments to verify the actual applicability of the proposed methods. The first model starts from an image captured from the environment and it applies a CA to perform the calculation of distances between free cells and the goal. The second model uses robot sensors to identify its neighborhood and it applies CA transition rules to determine the next movements. Some limitations which prevented the robots obtain good results in simulation were identified and improvements to the original models were applied. At the end, both new models exhibited better behaviors than their precursors in several scenarios. Aiming to validate our results, two simulation environments were employed (V-REP and Webots) and some experiments with e-puck robots were performed. No problema do planejamento de caminhos para robôs autônomos, o objetivo é encontrar uma lista de passos a serem aplicados para se obter um caminho entre o ponto inicial e a meta. Este trabalho visa a investigação e implementação de modelos baseados em autômatos celulares (ACs) para o planejamento de caminhos. Em uma fase inicial, foi realizado um estudo comparativo entre os métodos de planejamento de caminhos baseados em autômatos celulares publicados na literatura. Posteriormente, foram escolhidos dois trabalhos publicados que foram implementados em ambientes de simulação para se verificar a real aplicabilidade dos métodos propostos. O primeiro modelo parte de uma imagem capturada do ambiente de navegação e utiliza um AC para fazer o cálculo das distâncias entre as células livres e a meta. O segundo modelo utiliza os sensores do robô para identificar sua vizinhança a cada instante e utiliza regras de transição de ACs para determinar os próximos movimentos. Algumas limitações que impossibilitaram que os robôs obtivessem bons resultados em simulação foram identificadas e melhorias foram aplicadas aos modelos originais. Ao final, os dois novos modelos propostos exibiram um melhor desempenho do que seus precursores em diversos cenários. Para validar nossos resultados, dois ambientes de simulação foram empregados (V-REP e Webots), além da execução de alguns experimentos com robôs e-puck. Mestre em Ciência da Computação

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Switzer, Barbara T. "Robotic path planning with obstacle avoidance /." Online version of thesis, 1993. http://hdl.handle.net/1850/11712.

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Karamanlis, Vasilios. "Mulltivariate motion planning of autonomous robots." Thesis, Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/8705.

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A problem of motion control in robot motion planning is to find a smooth transition while going from one path to another. The key concept of our theory is the steering function, used to manipulate the motion of our vehicle. The steering function determines the robot's position and orientation by controlling path curvature and speed. We also present the - neutral switching method - algorithm that provides the autonomous vehicle with the capability to determine the best leaving point which allows for a smooth transition from one path to another in a model-based polygonal world. The above mentioned algorithm is thoroughly presented, analyzed, and programmed on a Unix workstation, and on the autonomous mobile robot Yamabico. The research data indicate that neutral switching method improved the transition results for polygon tracking, star tracking motion, and circle tracking. Moreover, neutral switching method enhances robot control and provides a more stable transition between paths than any previously known algorithm

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McKeever, Scott Douglas 1976. "Path planning for an autonomous vehicle." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8741.

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Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2000. Includes bibliographical references (p. 163-164). The desire for highly capable unmanned autonomous vehicles (UAVs), has necessitated the need for more research into the problems faced by these vehicles. One classic problem faced by UAVs concerns how the vehicle should traverse its environment in order to leave the current position and arrive at a desired location. The path to this goal location must maneuver the vehicle around any obstacles and reach the goal with minimal cost. A variant of this problem tasks the UAV with tracking a moving target. In this manner the UAVs trajectory is updated through time to reflect changes in the target's location. The specific mission addressed in this thesis, is the track and trail mission. This mission tasks a UAV with acquiring a target vehicle and tracking the vehicle for an indefinite period of time. The goal of this mission is not to intercept the vehicle, but to follow the target from a certain standoff distance. One can imagine many applications of this mission. One such application envisioned by the United States Navy deals with an unmanned underwater vehicle (UUV), tracking an enemy submarine. In addition, marine biologists could use such a capability to allow a UUV to follow and record valuable information on certain species. Planning these paths is conceptualized as a series of network shortest path problems. This thesis focuses on planning paths in the plane where the state of the vehicle is defined only by its position in space. In addition, a trajectory smoothing or path-smoothing component is addressed to eliminate any slope discontinuities as a result of the shortest path algorithms. A framework for the moving target shortest path problem is created. The resulting path planner is capable of performing the stated mission. A detailed simulation of the path planner operating on a UUV in an underwater environment is created in order to test the planner's performance. Different variants of the path planner are created in order to deal with different problem parameters. The resulting path planner is shown to be adaptable to these different conditions and effective at tracking a moving target. by Scott Douglas McKeever. S.M.

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Shanmugavel, M. "Path planning of multiple autonomous vehicles." Thesis, Cranfield University, 2007. http://hdl.handle.net/1826/1745.

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Safe and simultaneous arrival of constant speed, constant altitude UAVs on target is solved by design of paths of equal lengths. The starting point of the solution is the well-known Dubins path which is composed of circular arcs and line segments, thus requiring only one simple manoeuvre - constant rate turn. An explicit bound can be imposed on the rate during the design and the resulting paths are the minimum time solution of the problem. However, transition between arc and line segment entails discontinuous changes in lateral accelerations (latax), making this approach impractical for real fixed wing UAVs. Therefore, the Dubins solution is replaced with clothoid and also a novel one, based on quintic Pythagorean Hodograph (PH) curves, whose latax demand is continuous. The clothoid solution is direct as in the case of the Dubins path. The PH path is chosen for its rational functional form. The clothoid and the PH paths are designed to have lengths close to the lengths of the Dubins paths to stay close to the minimum time solution. To derive the clothoid and the PH paths that way, the Dubins solution is first interpreted in terms of Differential Geometry of curves using the path length and curvature as the key parameters. The curvature of a Dubins path is a piecewise constant and discontinuous function of its path length, which is a differential geometric expression of the discontinuous latax demand involved in transitions between the arc and the line segment. By contrast, the curvature of the PH path is a fifth order polynomial of its path length. This is not only continuous, also has enough design parameters (polynomial coefficients) to meet the latax (curvature) constraints (bounds) and to make the PH solution close to the minimum time one. The offset curves of the PH path are used to design a safety region along each path. The solution is simplified by dividing path planning into two phases. The first phase produces flyable paths while the second phase produces safe paths. Three types of paths are used: Dubins, clothoid and Pythagorean Hodograph (PH). The paths are produced both in 2D and 3D. In two dimensions, the Dubins path is generated using Euclidean and Differential geometric principles. It is shown that the principles of Differential geometry are convenient to generalize the path with the curvature. Due to the lack of curvature continuity of the Dubins path, paths with curvature continuity are considered. In this respect, initially the solution with the Dubins path is extended to produce clothoid path. Latter the PH path is produced using interpolation technique. Flyable paths in three dimensions are produced with the spatial Dubins and PH paths. In the second phase, the flyable paths are tuned for simultaneous arrival on target. The simultaneous arrival is achieved by producing the paths of equal lengths. Two safety conditions: (i) minimum separation distance and (ii) non-intersection of paths at equal distance are defined to maneuver in free space. In a cluttered space, an additional condition, threat detection and avoidance is defined to produce safe paths. The tuning is achieved by increasing the curvature of the paths and by creating an intermediate way-point. Instead of imposing safety constraints, the flyable paths are tested for meeting the constraints. The path is replanned either by creating a new way-point or by increasing the curvature between the way-points under consideration. The path lengths are made equal to that of a reference path.

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Shanmugavel, Madhavan. "Path planning of multiple autonomous vehicles." Thesis, Cranfield University, 2007. http://dspace.lib.cranfield.ac.uk/handle/1826/1745.

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Safe and simultaneous arrival of constant speed, constant altitude UAVs on target is solved by design of paths of equal lengths. The starting point of the solution is the well-known Dubins path which is composed of circular arcs and line segments, thus requiring only one simple manoeuvre - constant rate turn. An explicit bound can be imposed on the rate during the design and the resulting paths are the minimum time solution of the problem. However, transition between arc and line segment entails discontinuous changes in lateral accelerations (latax), making this approach impractical for real fixed wing UAVs. Therefore, the Dubins solution is replaced with clothoid and also a novel one, based on quintic Pythagorean Hodograph (PH) curves, whose latax demand is continuous. The clothoid solution is direct as in the case of the Dubins path. The PH path is chosen for its rational functional form. The clothoid and the PH paths are designed to have lengths close to the lengths of the Dubins paths to stay close to the minimum time solution. To derive the clothoid and the PH paths that way, the Dubins solution is first interpreted in terms of Differential Geometry of curves using the path length and curvature as the key parameters. The curvature of a Dubins path is a piecewise constant and discontinuous function of its path length, which is a differential geometric expression of the discontinuous latax demand involved in transitions between the arc and the line segment. By contrast, the curvature of the PH path is a fifth order polynomial of its path length. This is not only continuous, also has enough design parameters (polynomial coefficients) to meet the latax (curvature) constraints (bounds) and to make the PH solution close to the minimum time one. The offset curves of the PH path are used to design a safety region along each path. The solution is simplified by dividing path planning into two phases. The first phase produces flyable paths while the second phase produces safe paths. Three types of paths are used: Dubins, clothoid and Pythagorean Hodograph (PH). The paths are produced both in 2D and 3D. In two dimensions, the Dubins path is generated using Euclidean and Differential geometric principles. It is shown that the principles of Differential geometry are convenient to generalize the path with the curvature. Due to the lack of curvature continuity of the Dubins path, paths with curvature continuity are considered. In this respect, initially the solution with the Dubins path is extended to produce clothoid path. Latter the PH path is produced using interpolation technique. Flyable paths in three dimensions are produced with the spatial Dubins and PH paths. In the second phase, the flyable paths are tuned for simultaneous arrival on target. The simultaneous arrival is achieved by producing the paths of equal lengths. Two safety conditions: (i) minimum separation distance and (ii) non-intersection of paths at equal distance are defined to maneuver in free space. In a cluttered space, an additional condition, threat detection and avoidance is defined to produce safe paths. The tuning is achieved by increasing the curvature of the paths and by creating an intermediate way-point. Instead of imposing safety constraints, the flyable paths are tested for meeting the constraints. The path is replanned either by creating a new way-point or by increasing the curvature between the way-points under consideration. The path lengths are made equal to that of a reference path.

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47

Wooden, David T. "Graph-based Path Planning for Mobile Robots." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-11092006-180958/.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2007. Magnus Egerstedt, Committee Chair ; Patricio Vela, Committee Member ; Ayanna Howard, Committee Member ; Tucker Balch, Committee Member ; Wayne Book, Committee Member.

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48

Furci, Michele <1988&gt. "Mobile Robots Control and Path Planning Strategies." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amsdottorato.unibo.it/7511/.

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Mobile robots gained lots of attention in the last decades. Because of its flexibility and increased capabilities of automation, mobile robots are used in many applications: from domotic, to search and rescue missions, to agriculture, environment protection and many more. The main capability of mobile robots to accomplish a mission is the mobility in the work environment. To move in a certain environment the robots should achieve: guidance, navigation and control. This thesis focuses on guidance and control of mobile robots, with application to certain classes of robots: Vertical Take Off and Landing Unmanned Aerial Vehicles (VTOL UAV) and Differential Wheel robots (DWR). The contribution of this thesis is on modeling and control of the two classes of robots, and on novel strategies of combined control and motion planning for kinodynamic systems. A new approach to model a class of multi-propeller VTOL is proposed, with the aim of generating a general model for a system as a composition of elementary modules such as actuators and payloads. Two control law for VTOL vehicles and DWR are proposed. The goal of the first is to generate a simple yet powerful control to globally asymptotically stabilize a VTOL for acrobatic maneuvers. The second is a simple saturated input control law for trajectory tracking of a DWR model in 2D. About planning, a novel approach to generate non-feasible trajectories for robots that still guarantees a correct path for kinodynamic planning is proposed. The goal is to reduce the runtime of planners to be used in real-time and realistic scenario. Moreover an innovative framework for mobile robots motion planning with the use of Discrete Event Systems theory is introduced. The two proposed approaches allow to build a global, robust, real-time, quasi-optimal, kinodynamic planner suitable for replanning.

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Hague, Tony. "Motion planning for autonomous guided vehicles." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358592.

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Yiğit, Konuralp. "Path planning methods for Autonomous Underwater Vehicles." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/67807.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 75-81). From naval operations to ocean science missions, the importance of autonomous vehicles is increasing with the advances in underwater robotics technology. Due to the dynamic and intermittent underwater environment and the physical limitations of autonomous underwater vehicles, feasible and optimal path planning is crucial for autonomous underwater operations. The objective of this thesis is to develop and demonstrate an efficient underwater path planning algorithm based on the level set method. Specifically, the goal is to compute the paths of autonomous vehicles which minimize travel time in the presence of ocean currents. The approach is to either utilize or avoid any type of ocean flows, while allowing for currents that are much larger than the nominal vehicle speed and for three-dimensional currents which vary with time. Existing path planning methods for the fields of ocean science and robotics are first reviewed, and the advantages and disadvantages of each are discussed. The underpinnings of the level set and fast marching methods are then reviewed, including their new extension and application to underwater path planning. Finally, a new feasible and optimal time-dependent underwater path planning algorithm is derived and presented. In order to demonstrate the capabilities of the algorithm, a set of idealized test-cases of increasing complexity are first presented and discussed. A real three-dimensional path planning example, involving strong current conditions, is also illustrated. This example utilizes four-dimensional ocean flows from a realistic ocean prediction system which simulate the ocean response to the passage of a tropical storm in the Middle Atlantic Bight region. by Konuralp Yiğit. S.M.

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