Dissertations / Theses on the topic 'Mobile robots'

This thesis describes the implementation of a hierarchical robot simulation environment which supports the design of robots with vision and mobility. A seeing robot model applies a classification expert system for visual identification of laboratory objects. The visual data acquisition algorithm used by the robot vision system has been developed to exploit multiple viewing distances and perspectives. Several different simulations have been run testing the visual logic in a laboratory environment. Much work remains to integrate the vision system with the rest of the robot system.

Les robots mobiles à roues orientables gagnent de la mobilité en employant des roues conventionnelles entièrement orientables, comportant deux joints actifs, un pour la direction et un autre pour la conduite. En dépit d'avoir seulement un degré de mobilité (DOM) (défini ici comme degrés de liberté instantanément autorisés DOF), correspondant à la rotation autour du centre de rotation instantané (ICR), ces robots peuvent effectuer des trajectoires planaires complexes de $ 2D $. Ils sont moins chers et ont une capacité de charge plus élevée que les roues non conventionnelles (par exemple, Sweedish ou Omni-directional) et, en tant que telles, préférées aux applications industrielles. Cependant, ce type de structure de robot mobile présente des problèmes de contrôle textit {basic} difficiles de la coordination de la direction pour éviter les combats d'actionneur, en évitant les singularités cinématiques (ICR à l'axe de la direction) et les singularités de représentation (du modèle mathématique). En plus de résoudre les problèmes de contrôle textit {basic}, cette thèse attire également l'attention et présente des solutions aux problèmes de textit {niveau d'application}. Plus précisément, nous traitons deux problèmes: la première est la nécessité de reconfigurer "de manière discontinue" les articulations de direction, une fois que la discontinuité dans la trajectoire du robot se produit. Une telle situation - la discontinuité dans le mouvement du robot - est plus susceptible de se produire de nos jours, dans le domaine émergent de la collaboration homme-robot. Les robots mobiles qui fonctionnent à proximité des travailleurs humains en mouvement rapide rencontrent généralement une discontinuité dans la trajectoire calculée en ligne. Le second apparaît dans les applications nécessitant que l'angle de l'angle soit maintenu, certains objets ou fonctionnalités restent dans le champ de vision (p. Ex., Pour les tâches basées sur la vision) ou les changements de traduction. Ensuite, le point ICR est nécessaire pour déplacer de longues distances d'un extrême de l'espace de travail à l'autre, généralement en passant par le centre géométrique du robot, où la vitesse du robot est limitée. Dans ces scénarios d'application, les contrôleurs basés sur l'ICR à l'état de l'art conduiront à des comportements / résultats insatisfaisants. Dans cette thèse, nous résolvons les problèmes de niveau d'application susmentionnés; à savoir la discontinuité dans les commandes de vitesse du robot et une planification meilleure / efficace pour le contrôle du mouvement du point ICR tout en respectant les limites maximales de performance des articulations de direction et en évitant les singularités cinématiques et représentatives. Nos résultats ont été validés expérimentalement sur une base mobile industrielle
Steerable wheeled mobile robots gain mobility by employing fully steerable conventional wheels, having two active joints, one for steering, and another for driving. Despite having only one degree of mobility (DOM) (defined here as the instantaneously accessible degrees of freedom DOF), corresponding to the rotation about the instantaneous center of rotation (ICR), such robots can perform complex $2D$ planar trajectories. They are cheaper and have higher load carrying capacity than non-conventional wheels (e.g., Sweedish or Omni-directional), and as such preferred for industrial applications. However, this type of mobile robot structure presents challenging textit{basic} control issues of steering coordination to avoid actuator fighting, avoiding kinematic (ICR at the steering joint axis) and representation (from the mathematical model) singularities. In addition to solving the textit{basic} control problems, this thesis also focuses attention and presents solutions to textit{application level} problems. Specifically we deal with two problems: the first is the necessity to "discontinuously" reconfigure the steer joints, once discontinuity in the robot trajectory occurs. Such situation - discontinuity in robot motion - is more likely to happen nowadays, in the emerging field of human-robot collaboration. Mobile robots working in the vicinity of fast moving human workers, will usually encounter discontinuity in the online computed trajectory. The second appears in applications requiring that some heading angle is to be maintained, some object or feature stays in the field of view (e.g., for vision-based tasks), or the translation verse changes. Then, the ICR point is required to move long distances from one extreme of the workspace to the other, usually passing by the robot geometric center, where the feasible robot velocity is limited. In these application scenarios, the state-of-art ICR based controllers will lead to unsatisfactory behavior/results. In this thesis, we solve the aforementioned application level problems; namely discontinuity in robot velocity commands, and better/efficient planning for ICR point motion control while respecting the maximum steer joint performance limits, and avoiding kinematic and representational singularities. Our findings has been validated experimentally on an industrial mobile base

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.

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Dr. Magnus Egerstedt; Committee Co-Chair: Dr. Ayanna Howard; Committee Member: Dr. David Taylor; Committee Member: Dr. Frank Dellaert; Committee Member: Dr. Ian Akyildiz; Committee Member: Dr. Jeff Shamma.

Thesis (M.S.)--West Virginia University, 1999.
Title from document title page. Document formatted into pages; contains viii, 122 p. : ill. Includes abstract. Includes bibliographical references (p. 57-59).

Thesis (M.S.)--University of Missouri--Rolla, 2007.
Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed February 13, 2008) Includes bibliographical references (p. 39-41).

Depuis la fin des années 1980, le développement de véhicules autonomes, capables de rouler sans l'intervention d'un être humain, est un champ de recherche très actif dans la plupart des grands pays industrialisés. La diminution du nombre d'accidents, des temps de trajet plus courts, une meilleure efficacité énergétique et des besoins en infrastructure plus limités, sont autant d'effets socio-économiques espérés de leur déploiement. Des formes de coopération inter-véhicules et entre les véhicules et l'infrastructure routière sont nécessaires au fonctionnement sûr et efficace du système de transport dans sa globalité. Cette thèse s'intéresse à une forme de coopération particulière en étudiant la coordination de robots mobiles aux intersections. La majorité des systèmes de coordination existants planifie une trajectoire que les robots doivent exécuter afin d'assurer l'absence de collision. C'est une approche classique de la planification, qui est alors considérée comme un mécanisme de génération de l'action. Dans cette thèse, seules les priorités entre les véhicules sont planifiées, c'est-à-dire l'ordre relatif de passage des véhicules dans l'intersection, ce qui est bien plus faible car un grand nombre de trajectoires respectent les même priorités. Les priorités sont alors simplement utilisées comme une ressource de coordination pour guider les robots dans l'intersection. Une fois les priorités affectées, les robots suivent une loi de contrôle qui s'assure qu'elles soient bien respectées. Il en découle un système de coordination robuste, capable de gérer toute une classe d'événements imprévisibles de façon réactive, ce qui est particulièrement adapté pour une application à la coordination de véhicules autonomes aux intersections où voitures, transports en commun et piétons partagent la route
Since the end of the 1980's, the development of self-driven autonomous vehicles is an intensive research area in most major industrial countries. Positive socio-economic potential impacts include a decrease of crashes, a reduction of travel times, energy efficiency improvements, and a reduced need of costly physical infrastructure. Some form of vehicle-to-vehicle and/or vehicle-to-infrastructure cooperation is required to ensure a safe and efficient global transportation system. This thesis deals with a particular form of cooperation by studying the problem of coordinating multiple mobile robots at an intersection area. Most of coordination systems proposed in previous work consist of planning a trajectory and to control the robots along the planned trajectory: that is the plan-as-program paradigm where planning is considered as a generative mechanism of action. The approach of the thesis is to plan priorities – the relative order of robots to go through the intersection – which is much weaker as many trajectories respect the same priorities. Then, priorities are merely used as a coordination resource to guide robots through the intersection. Once priorities are assigned, robots are controlled through a control law preserving the assigned priorities. It results in a more robust coordination system – able to handle a large class of unexpected events in a reactive manner – particularly well adapted for an application to the coordination of autonomous vehicles at intersections where cars, public transport and pedestrians share the road

In this thesis, we study how and to what extent a self-organized mobile robot flock can be guided by informing some of the robots within the flock about a preferred direction of motion. Specifically, we extend a flocking behavior that was shown to maneuver a swarm of mobile robots as a cohesive group in free space, avoiding obstacles. In its original form, this behavior does not have a preferred direction and the flock would wander aimlessly. In this study, we incorporate a preference for a goal direction in some of the robots. These informed robots do not signal that they are informed (a.k.a. unacknowledged leadership) and instead guide the swarm by their tendency to move in the desired direction. Through experimental results with physical and simulated robots we show that the self-organized flocking of a robot swarm can be effectively guided by an informed minority of the flock. We evaluate the system using a number of quantitative metrics: First, we propose to use the mutual information metric from Information Theory as a dynamical measure of the information exchange. Then, we discuss the accuracy metric from directional statistics and size of the largest cluster as the measures of system performance. Using these metrics, we perform analyses from two points of views: In the transient analyses, we demonstrate the information exchange between the robots as the time advances, and the increase in the accuracy of the flock when the conditions are suitable for an adequate amount of information exchange. In the steady state analyses, we investigate the interdependent effects of the size of the flock in terms of the robots in it, the ratio of informed robots in the flock over the total flock size, the weight of the direction preference behavior, and the noise in the system.

Robotics is an interdisciplinary subject and combines mechanical, computer and electrical engineering components together to solve different kinds of problems. In order to build robotic systems, these disciplines should be integrated. Therefore, mobile robots can be used as a tool in education for teaching engineering concepts. They can be employed to be used in undergraduate, graduate and doctorate research. Hands on experience on a mobile robot increase motivation of the students on the topic and give them precious practical knowledge. It also delivers students new skills like teamwork, problem solving, creativity, by executing robotic exercises. To be able to fulfill these outcomes, universities and research centers need mobile robot platforms that are modular, easy to build, cheap and flexible. However it should be also powerful and capable of being used in different research studies and hence be customizable depending on the requirements of these topics. This thesis aims at building an indoor mobile robot that can be used as a platform for developing algorithms involving various sensors incorporated onto a mobile platform. More precisely, it can be used as a base for indoor navigation and localization algorithms, as well as it can be used as platform for developing algorithms for larger autonomous mobile robots. The thesis work involves the design and manufacturing of a mobile robot platform that can potentially facilitate mobile robotics research that involves use of various hardware to develop and test different perception and navigation algorithms.

Thesis (Ph.D.)--City University of Hong Kong, 2009.
"Submitted to Department of Manufacturing Engineering and Engineering Management in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves 87-100)

After decades of unrealistic predictions and expectations, robots have finally escaped from industrial workplaces and made their way into our homes,offices, museums and other public spaces. These service robots are increasingly present in our environments and many believe that it is in the area ofservice and domestic robotics that we will see the largest growth within thenext few years. In order to realize the dream of robot assistants performing human-like tasks together with humans in a seamless fashion, we need toprovide them with the fundamental capability of understanding complex, dynamic and unstructured environments. More importantly, we need to enablethem the sharing of our understanding of space to permit natural cooper-ation. To this end, this thesis addresses the problem of building internalrepresentations of space for artificial mobile agents populated with humanspatial semantics as well as means for inferring that semantics from sensoryinformation. More specifically, an extensible approach to place classificationis introduced and used for mobile robot localization as well as categorizationand extraction of spatial semantic concepts from general place appearance andgeometry. The models can be incrementally adapted to the dynamic changesin the environment and employ efficient ways for cue integration, sensor fu-sion and confidence estimation. In addition, a system and representationalapproach to semantic mapping is presented. The system incorporates and in-tegrates semantic knowledge from multiple sources such as the geometry andgeneral appearance of places, presence of objects, topology of the environmentas well as human input. A conceptual map is designed and used for modelingand reasoning about spatial concepts and their relations to spatial entitiesand their semantic properties. Finally, the semantic mapping algorithm isbuilt into an integrated robotic system and shown to substantially enhancethe performance of the robot on the complex task of active object search. Thepresented evaluations show the effectiveness of the system and its underlyingcomponents and demonstrate applicability to real-world problems in realistichuman settings.
QC 20110527

In this thesis two methods to solve the Simultaneous Localization And Mapping problem are presented. The classical extended Kalman filter is used as a reference from where an efficient particle filter is examined, which uses deterministic samples called sigma points. Most of the effort is put on implementing these algorithms together with the Symmetries and Permutations Model, but a preliminary comparison of the methods has been done as well. Experiments show that linearization errors make the map inaccurate over long periods of time, and methods are discussed which decrease these effects.

The problem addressed in this thesis is discrimination of gases with an array of partially selective gas sensors. Metal oxide gas sensors are the most common gas sensing technology since they have, compared to other gas sensing technologies, a high sensitivity to the target compounds, a fast response time,they show a good stability of the response over time and they are commercially available. One of the most severe limitation of metal oxide gas sensors is the scarce selectivity, that means that they do not respond only to the compound for which they are optimized but also to other compounds. One way to enhance the selectivity of metal oxide gas sensors is to build an array of sensorswith different, and partially overlapping, selectivities and then analyze the response of the array with a pattern recognition algorithm. The concept of anarray of partially selective gas sensors used together with a pattern recognition algorithm is known as an electronic nose (e-nose).In this thesis the attention is focused on e-nose applications related mobile robotics. A mobile robot equipped with an e-nose can address tasks like environmental monitoring, search and rescue operations or exploration of hazardous areas. In e-noses mounted on mobile robots the sensing array is most often directly exposed to the environment without the use of a sensing chamber.This choice is often made because of constraints in weight, costs and because the dynamic response obtained by the direct interaction of the sensors with the gas plume contains valuable information. However, this setup introduces additional challenges due to the gas dispersion that characterize natural environments.Turbulent and chaotic gas dispersal causes the array of sensors to be exposed to rapid changes in concentration that cause the sensor response to behighly dynamic and to seldom reach a steady state. Therefore the discriminationof gases has to be performed on features extracted from the dynamics of the signal. The problem is further complicated by variations in temperature and humidity, physical variables to which metal oxide gas sensors are crossensitive.For these reasons the problem of discrimination of gases when an array of sensors is directly exposed to the environment is different from when the array of sensors is in a controlled chamber. This thesis is a compilation of papers whose contributions are two folded.On one side new algorithms for discrimination of gases with an array of sensors directly exposed to the environment are presented. On the other side, innovative experimental setups are proposed. These experimental setups enable the collection of high quality data that allow a better insight in the problem of discrimination of gases with mobile robots equipped with an e-nose. The algorithmic contributions start with the design and validation of a gas discrimination algorithm for gas sensors array directly exposed to the environment. The algorithmis then further developed in order to be able to run online on a robot, thereby enabling the possibility of creating an olfactory driven path-planning strategy. Additional contributions aim at maximizing the generalization capabilitiesof the gas discrimination algorithm with respect to variations in the environmental conditions. First an approach in which the odor discrimination is performed by an ensemble of linear classifiers is considered. Then a feature selection method that aims at finding a feature set that is insensitive to variations in environmental conditions is designed. Finally, a further contribution in this thesis is the design of a pattern recognition algorithm for identification of bacteria from blood vials. In this case the array of gas sensors was deployed ina controlled sensing chamber.

This work proposes a biologically inspired collective behaviour for a team of co-operating robots. Collective behaviour is achieved by controlling the local interactions among a set of identical mobile robots, each robot performing a set of simple behaviours in order to realise group goals. A modification of the subsumption architecture is proposed for implementing control of individual robots. This architecture is adopted because it is computationally inexpensive and potentially suitable for low-level reactive and reflexive behaviours. In this scenario, the individual behaviours of the robots have different aims, which may cause conflict. To address this issue, a fuzzy logic-based approach for multiple behaviour coordination within each robot is proposed. The work also focuses on the development of intelligent multi-agent robot teams capable of acting autonomously and of collaborating in a dynamic environment to achieve team objectives. A knowledge-based software architecture is proposed that enables these robots to select co-operative behaviours and to adapt their performance during the specified time of the mission. These abilities are important because of uncertainties in the environmental conditions and because of possible functional failures in some team members. Improvement in team performance is achieved by updating the control of the robots based on knowledge acquired on-line. This architecture is implemented in a simulated team of mobile robots performing a proof-of-concept collaborative task. The results show a significant improvement in overall group performance and the robot team is able to achieve adaptive cooperative control despite dynamic changes in the environment and variation in the capabilities of the team members. Finally, a task involving real mobile robots is undertaken to demonstrate a practical, though simplified, implementation of the proposed collective behaviour.

In mobile robot applications navigation systems are of great importance. Automation of mobile robots demands robust navigation systems. This thesis deals with a few solutions on how to help a mobile robot navigate in an environment. Navigation systems using retroreflective beacons and applications relying on laser range finders are two different solutions to aid a mobile robot. The first type of system provides very robust navigation, with the use of extra infrastructure in the environment. The latter has no need for any extra infrastructure as it can use the structure in the surrounding environment. Navigation using dead reckoning and GPS systems are also discussed. Furthermore, some of the mobile robot platforms available at Luleå University of Technology, and their application are presented.
Godkänd; 2007; 20071113 (ysko)
CASTT - Centre for Automotive Systems Technologies and Testing

Mestrado em Engenharia Eletrónica e Telecomunicações
Automação, na mais simples das designações, é a arte de criar vida na máquina, possibilitando certas ações sem controlo directo por parte de um utilizador. Esta área de estudo permite que certas atividades que consideramos aborrecidas ou perigosas possam ser executadas por máquinas. Nesta tese, um estudo do estado da arte no campo de robôs móveis e inteligentes foi realizado, apresentando um focus especial em algoritmos de navegação baseados em procura e amostragem. Uma simulação foi desenvolvida, na qual um modelo do robô Wiserobot foi criado, utilizado como ambiente de teste um ed cio conhecido no campo da robótica, o laboratório da Willow Garage. Nesta simulação foram realizados testes aos algoritmos explorados anteriormente, nomeadamente Dijkstra, PRM e RRT. Para testar os algoritmos por amostragem, um plug-in foi desenvolvido para utilizar a Open Motion Planning Library para avaliar resultados dos mesmos. Por fim, código foi desenvolvido, usando e tendo por base bibliotecas existentes no ROS, de modo a dar ao nosso modelo do robô capacidades de navegação no ambiente simulado, inicialmente estático seguido de testes com objectos não declarados. Os resultados dos vários planeadores foram comparados para avaliar a prestação nos casos de testes definidos, utilizando métricas escolhidas previamente.
Automation, in the simplest of designations, is the art of creating life in the machine, allowing the performance of certain actions without the need of direct control by an user. This area of study allows for certain activities that we deem as tedious or dangerous to be executed by machines. In this thesis, a study of the state of the art in the eld of mobile and autonomous robotics is made, focusing in navigation algorithms based on search and sampling. A simulation was developed, in which a model of the robot was created, to be used with an environment well know by roboticist, Willow Garage. In this simulation, tests were made to the algorithms explored earlier, namely Dijkstra, PRM and RRT. To test multiple samplebased planners, a plug-in was developed to use the Open Motion Planning Library for benchmarking purposes. Finally code is developed, based and using existing ROS packages, to give a model cargo robot navigation capabilities in a simulated indoor environment, initially static then with undeclared obstacles. The results were compared from multiple planners to evaluate the performance in the test cases de ned, using pre-established metrics.

This thesis deals with various aspects of indoor navigationfor mobile robots. For a system that moves around in ahousehold or office environment,two major problems must betackled. First, an appropriate control scheme has to bedesigned in order to navigate the platform. Second, the form ofrepresentations of the environment must be chosen.

Behaviour based approaches have become the dominantmethodologies for designing control schemes for robotnavigation. One of them is the dynamical systems approach,which is based on the mathematical theory of nonlineardynamics. It provides a sound theoretical framework for bothbehaviour design and behaviour coordination. In the workpresented in this thesis, the approach has been used for thefirst time to construct a navigation system for realistic tasksin large-scale real-world environments. In particular, thecoordination scheme was exploited in order to combinecontinuous sensory signals and discrete events for decisionmaking processes. In addition, this coordination frameworkassures a continuous control signal at all times and permitsthe robot to deal with unexpected events.

In order to act in the real world, the control system makesuse of representations of the environment. On the one hand,local geometrical representations parameterise the behaviours.On the other hand, context information and a predefined worldmodel enable the coordination scheme to switchbetweensubtasks. These representations constitute symbols, on thebasis of which the system makes decisions. These symbols mustbe anchored in the real world, requiring the capability ofrelating to sensory data. A general framework for theseanchoring processes in hybrid deliberative architectures isproposed. A distinction of anchoring on two different levels ofabstraction reduces the complexity of the problemsignificantly.

A topological map was chosen as a world model. Through theadvanced behaviour coordination system and a proper choice ofrepresentations,the complexity of this map can be kept at aminimum. This allows the development of simple algorithms forautomatic map acquisition. When the robot is guided through theenvironment, it creates such a map of the area online. Theresulting map is precise enough for subsequent use innavigation.

In addition, initial studies on navigation in human-robotinteraction tasks are presented. These kinds of tasks posedifferent constraints on a robotic system than, for example,delivery missions. It is shown that the methods developed inthis thesis can easily be applied to interactive navigation.Results show a personal robot maintaining formations with agroup of persons during social interaction.

Keywords:mobile robots, robot navigation, indoornavigation, behaviour based robotics, hybrid deliberativesystems, dynamical systems approach, topological maps, symbolanchoring, autonomous mapping, human-robot interaction

Cette thèse présente un nouveau concept de robots parallèles à câble mobile (RPCM) comme un nouveau système robotique. RPCM est composé d'un robot parallèle à câble (RPC) classique monté sur plusieurs bases mobiles. Les RPCMs combinent l'autonomie des robots mobiles avec les avantages des RPCs, à savoir un grand espace de travail, un rapport charge utile/poids élevé, une faible inertie de l'effecteur final, une capacité de déploiement et une reconfigurabilité. De plus, les RPCMs présentent une nouvelle innovation technique qui pourrait contribuer à apporter plus de flexibilité et de polyvalence par rapport aux solutions robotiques industrielles existantes. Deux prototypes de RPCMs appelés FASTKIT et MoPICK ont été développés au cours de cette thèse. FASTKIT est composé de deux bases mobiles portant une plate-forme mobile à six degrés de liberté, tirée par huit câbles, dans le but de fournir une solution robotique économique et polyvalente pour la logistique. MoPICK est composé d'une plate-forme mobile à trois degrés de liberté tirée par quatre câbles montés sur quatre bases mobiles. Les applications ciblées de MoPICK sont des tâches mobiles dans un environnement contraint, par exemple un atelier ou des opérations logistiques dans un entrepôt. Les contributions de cette thèse sont les suivantes. Tout d'abord, toutes les conditions nécessaires à l'atteinte de l'équilibre statique d'un RPCM sont étudiées. Ces conditions sont utilisées pour développer un algorithme de distribution de tension pour le contrôle en temps réel des câbles RPCM. Les conditions d'équilibre sont également utilisées pour étudier l'espace de travail clé en main des RPCMs. Ensuite, les performances cinématiques et les capacités de torsion des RPCMs sont étudiées. Enfin, la dernière partie de la thèse présente des stratégies de planification de trajectoires multiples pour les RPCMs afin de reconfigurer l'architecture géométrique du RPC pour réaliser la tâche souhaitée
This thesis presents a novel concept of Mobile Cable - Driven Parallel Robots (MCDPRs) as a new robotic system. MCDPR is composed of a classical C able - D riven P a rallel R obot (CDPR) mounted on multiple mobile bases. MCDPRs combines the autonomy of mobile robots with the advantages of CDPRs, namely, large workspace, high payload - to - weight ratio, low end - effector inertia, deployability and reconfigurability. Moreover , MCDPRs presents a new technical innovation that could help to bring more flexibility and versatility with respect to existing industrial robotic solutions. Two MCDPRs prototypes named FASTKIT and MoPICK have been developed during the course of this the sis. FASTKIT is composed of two mobile bases carrying a six degrees - of - freedom moving - platform, pulled by eight cables , with a goal to provide a low cost and versatile robotic solution for logistics. MoPICK is composed of a three degrees - of - freedom movi ng - platform pulled by four cables mounted on four mobile bases. The targeted applications of MoPICK are mobile tasks in a constrained environment, for example, a workshop or logistic operations in a warehouse. The contributions of this thesis are as follow s. Firstly, all the necessary conditions are studied that required to achieve the static equilibrium of a MCDPR . These conditions are used to develop a Tension Distribution Algorithm for the real time control of the MCDRP cables. The equilibrium conditions are also used to investigate the Wrench - Feasible - Workspace of MCDPRs. Afterwards, the kinematic performance and twist capabilities of the MCDPRs are investigated. Finally, the last part of the thesis presents multiple path planning strategies for MCDPRs i n order to reconfigure the CDPR’s geometric architecture for performing the desired task

The major problem of robotics research today is that there is a barrier to entry into robotics research. Robot system software is complex and a researcher that wishes to concentrate on one particular problem often needs to learn about details, dependencies and intricacies of the complete system. This is because a robot system needs several different modules that need to communicate and execute in parallel.

Today there is not much controlled comparisons of algorithms and solutions for a given task, which is the standard scientific method of other sciences. There is also very little sharing between groups and projects, requiring code to be written from scratch over and over again.

This thesis proposes a general framework for robotics. By examining successful systems and architectures of past and present, yields a number of key properties. Some of these are ease of use, modularity, portability and efficiency. Even though there is much consensus on that the hybrid deliberate/reactive is the best architectural model that the community has produced so far, a framework should not stipulate a specific architecture. Instead the framework should enable the building of different architectures. Such a scheme implies that the modules are seen as common peers and not divided into clients and servers or forced into a set layering.

Using a standardized middleware such as CORBA, efficient communication can be carried out between different platforms and languages. Middleware also provides network transparency which is valuable in distributed systems. Component-based Software Engineering (CBSE) is an approach that could solve many of the aforementioned problems. It enforces modularity which helps to manage complexity. Components can be developed in isolation, since algorithms are encapsulated in components where only the interfaces need to be known by other users. A complete system can be created by assembling components from different sources.

Comparisons and sharing can greatly benefit from CBSE. A component-based framework called ORCA has been implemented with the following characteristics. All communication is carried out be either of three communication patterns, query, send and push. Communication is done using CORBA, although most of the CORBA code is hidden for the developer and can in the future be replaced by other mechanisms. Objects are transported between components in the form of the CORBA valuetype.

A component model is specified that among other things include support for a state-machine. This also handles initialization and sets up communication. Configuration is achieved by the presence of an XML-file per component. A hardware abstraction scheme is specified that basically route the communication patterns right down to the hardware level.

The framework has been verified by the implementation of a number of working systems.

In the future, robots will expand from industrial and research applications to the home. Domestic service robots will work in the home to perform useful tasks such as object retrieval, cleaning, organization, and security. The tireless support of these systems will not only enable able bodied people to avoid mundane chores; they will also enable the elderly to remain independent from institutional care by providing service, safety, and companionship. Robots will need to understand the relationship between objects and their environments to perform some of these tasks. Structured indoor environments are organized according to architectural guidelines and convenience for their residents. Utilizing this information makes it possible to predict the location of objects. Conversely, one can also predict the function of a room from the detection of a few objects within a given space. This thesis introduces a framework for combining object permanence and context called the probabilistic cognitive model. This framework combines reasoning about spatial extent of places and the identity of objects and their relationships to one another and to the locations where they appear. This type of reasoning takes into account the context in which objects appear to determine their identity and purpose. The probabilistic cognitive model combines a mapping system called OmniMapper with a conditional random field probabilistic model for context representation. The conditional random field models the dependencies between location and identity in a real-world domestic environment. This model is used by mobile robot systems to predict the effects of their actions during autonomous object search tasks in unknown environments.

With current state-of-the-art approaches, development of a single mobile manipulation capability can be a labor-intensive process that presents an impediment to the creation of general purpose household robots. At the same time, we expect that involving a larger community of non-roboticists can accelerate the creation of new novel behaviors. We introduce the use of a software authoring environment called ROS Commander (ROSCo) allowing end-users to create, refine, and reuse robot behaviors with complexity similar to those currently created by roboticists. Akin to Photoshop, which provides end-users with interfaces for advanced computer vision algorithms, our environment provides interfaces to mobile manipulation algorithmic building blocks that can be combined and configured to suit the demands of new tasks and their variations. As our system can be more demanding of users than alternatives such as using kinesthetic guidance or learning from demonstration, we performed a user study with 11 able-bodied participants and one person with quadriplegia to determine whether computer literate non-roboticists will be able to learn to use our tool. In our study, all participants were able to successfully construct functional behaviors after being trained. Furthermore, participants were able to produce behaviors that demonstrated a variety of creative manipulation strategies, showing the power of enabling end-users to author robot behaviors. Additionally, we introduce how using autonomous robot learning, where the robot captures its own training data, can complement human authoring of behaviors by freeing users from the repetitive task of capturing data for learning. By taking advantage of the robot's embodiment, our method creates classifiers that predict using visual appearances 3D locations on home mechanisms where user constructed behaviors will succeed. With active learning, we show that such classifiers can be learned using a small number of examples. We also show that this learning system works with behaviors constructed by non-roboticists in our user study. As far as we know, this is the first instance of perception learning with behaviors not hand-crafted by roboticists.

We study vertical jumping in a simple robot comprising an actuated mass spring arrangement. The actuator frequency and phase are systematically varied to find optimal performance. Optimal jumps occur above and below (but not at) the robot's resonant frequency f0. Two distinct jumping modes emerge: a simple jump which is optimal above f0 is achievable with a squat maneuver, and a peculiar stutter jump which is optimal below f0 is generated with a countermovement. A simple dynamical model reveals how optimal lift-off results from non-resonant transient dynamics.

Orientador: Marco Antonio Robert Alves
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: Este trabalho visa o desenvolvimento de uma plataforma básica com o propósito de ser-vir de estrutura para aplicações em robôs móveis. Esta plataforma consta de módulos de comunicação para o meio exterior (Bluetooth, WiFi e ZigBee) e com um barramento de comunicação interior que permite a inclusão de módulos que controlam sensores e atuadores (sensores como de distância, câmeras de vídeo, GPS, Bussola digital, acelerômetros, umidade, temperatura, pressão, etc., e atuadores como motores, servos, válvulas, etc.). A plataforma básica consta de protocolos de comunicação e um set de comandos tanto nas comunicações via rádio como no barramento interno o que permite o desenvolvimento de novas aplicações. O software interno, também é um software de código aberto que permite aos pesquisadores, hobbistas, profissionais, alunos e professores modificar e desenvolver qualquer tipo de aplicação tanto para que a plataforma seja montada em estruturas diferentes como também o desenvolvimento de software desktop para comando do robô via internet, celular ou qualquer tipo de tele-comunicação futura. Com este trabalho se pretende preencher um vazio que fará viável sua aplicação nas áreas de educação básica, esta não apenas nas disciplinas tradicionais, como Matemática e Geografia, mas também em disciplinas transversais, nas quais os alunos poderão aprender a programar rotinas para educação no trânsito, seleção de lixo reciclável, ecologia (reconhecimento de águas), inclusão social e reconhecimentos de MAPas, utilizando sistemas de programação em blocos. No caso dos pesquisadores e hobbistas, os produtos seriam utilizados para o desenvolvimento de novos módulos e outras aplicações mais sofisticadas, podendo tudo isso ser realizado via tele-operação. Como foi desenvolvido um único sistema a ser usado tanto na educação básica quanto para pesquisas de alto nível tecnológico, o sistema é flexível, possuindo um software com programação em blocos, para as escolas de ensino fundamental e médio; e um software com programação em C, para pesquisadores e hobbistas
Abstract: This study aims at developing a basic platform in order to provide a structure for applications in mobile robots. This platform consists of modules for communication to the outside world (Bluetooth, WiFi and ZigBee) and an internal communication bus that allows the inclusion of modules that control sensors and actuators (such as distance sensors, video cameras, GPS, digital compass , accelerometers, humidity, temperature, pressure, etc ... as motors and actuators, servos, valves, etc ...). The basic platform consists of communication protocols and a set of commands as much as radio communications in the internal bus that allows the development of new applications. The internal software is also an open source software that allows researchers, hobbyists, professionals, students and teachers to modify and develop any type of application for both the platform is mounted on different structures as well as the development of desktop software for remote control of robot via the Internet, mobile phone or any type of tele-communication future. This work is intended to fill a void that will make feasible its application in the areas of basic education, this not only in traditional disciplines such as math and geography, but also in cross-disciplines in which students can learn to program routines for traffic education, selection of recyclable waste, ecology recognition (water), social inclusion and recognition of MAPas using systems programming block. For researchers and hobbyists, the products would be used for the development of new modules and other more sophisticated applications, may all be performed via the teleoperation. Was developed as a single system to be used both in basic education and for research on high technology, the system is flexible, having a software programming blocks to the elementary schools and middle, and a software programming in C for researchers and hobbyists
Doutorado
Eletrônica, Microeletrônica e Optoeletrônica
Doutor em Engenharia Elétrica

Aquesta tesi tracta el problema de l'aprenentatge automàtic d'entorns estructurats n robòtica mòbil. Particularment, l'extracció de característiques a partir dels senyals dels sensors, la construcció autònoma de mapes, i l'autolocalització de robots.
S'estudien els fonaments matemàtics necessaris per a l'extracció de característiques a partir d'imatges i registres d'un làser, els quals permeten la identificació unívoca dels elements de l'entorn. Els atributs extrets a partir del senyal d'un sol sensor poden ser insuficients quan es volen caracteritzar els elements de l'entorn de forma invariant; això es pot millorar combinant informació de múltiples fonts. Es presenta un nou algorisme per la fusió d'informació complementaria extreta de dos mòduls de visió de baix nivell.
Aquesta fusió d'informació produeix descripcions més completes dels objectes de l'entorn, els quals poden ser seguits i apresos dins el context de la robòtica mòbil. Les variacions en les condicions d'il·luminació i les oclusions fan que l'associació de dades en visió per computador sigui una tasca difícil de completar.
Tot i això, l'ús de restriccions geomètriques i fotogramètriques permeten reduir la cerca de correspondències entre imatges successives; i al centrar l'atenció en un reduït nombre de característiques, aquestes poden ser seguides en imatges successives, simplificant així el problema d'associació de dades. Es recalquen les tècniques de la geometria de múltiples vistes que són rellevants pel còmput d'una estimació inicial de la posició dels elements de l'entorn, el que permet la reconstrucció del moviment del robot entre imatges successives; situació desitjable quan no existeix odometria o quan las seves lectures són poc fiables.
Quan els elements de l'entorn s'han extret i identificat, la segona part del problema consisteix en utilitzar aquestes observacions tant per estimar la posició del robot, com per refinar l'estimació dels mateixos elements de l'entorn. El moviment del robot i les lectures dels sensors es consideren com dos processos estocàstics, i el problema es tracta des del punt de vista de la teoria d'estimació, on el soroll inherent als sensors i al moviment del robot es consideren com a seqüències aleatòries.
El principal inconvenient existent en l'ús de tècniques d'estimació pel còmput concurrent de la posició del robot i la construcció d'un mapa, és que fins ara s'ha considerat la seva aplicació únicament en entorns estàtics, i que el seu ús en situacions més realistes ofereix poca robustesa. Es proposa un conjunt de funcions per avaluar la qualitat temporal de les observacions per tal de resoldre les situacions en que les observacions dels elements de l'entorn no siguin consistents en el temps. Es mostra com la utilització d'aquestes proves de qualitat temporal conjuntament amb les proves de compatibilitat espacial milloren els resultats quan es fen servir amb un mètode d'estimació òptima de la construcció concurrent de mapes i l'autolocalització de robots.
La idea principal consisteix en emprar un històric dels errors en l'associació de les dades per calcular la possibilitat d'incórrer en nous errors d'associació; i excloure del mapa aquells elements dels quals les observacions no siguin consistents.
Es posa especial atenció en el fet que l'eliminació dels elements inconsistents del mapa no violi les propietats dels algorismes de construcció concurrent de mapes i autolocalització descrits en la literatura; és a dir, convergència assimptòtica i correlació completa.
Aquesta tesi proporciona també un profund anàlisi del model de construcció concurrent de mapes i autolocalització totalment correlat des d'un punt de vista de la teoria de control de sistemes. Partint del fet que el filtre de Kalman no és més que un estimador òptim, s'analitzen les implicacions de tenir un vector d'estats que es revisa a partir de mesures totalment correladas.
Es revela de manera teòrica i amb experiments les limitacions d'utilitzar un enfocament per la construcció concurrent de mapes i l'autolocalització a partir de mesures totalment correladas.
El fet de tenir un model parcialment observable inhibeix la reconstrucció total de l'espai d'estats, produint tant mateix una estimació de la posició dels elements de l'entorn que depèn en tot cas de les observacions inicials, i que no garanteix la convergència a una matriu de covariància definida positivament.
D'altra banda, el fet de tenir un vector d'estats parcialment controlable fa que, desprès d'un reduït nombre d'iteracions el filtre cregui tenir una estimació perfecta de l'estat dels elements de l'entorn; amb els corresponents guanys de Kalman convergint a zero. Per tant, desprès d'un reduït nombre d'iteracions del filtre, els innovacions no s'utilitzen més. Es mostra com reduir els efectes de la correlació total i de la controlabilitat parcial. A més a més, suposant que el filtre de Kalman és un observador òptim per a la reconstrucció dels estats, és pertinent construir un regulador òptim que permeti conduir el robot el més a prop possible a una trajectòria desitjada durant la construcció d'un mapa. Es mostra com la dualitat existent entre l'observabilitat i la controlabilitat es pot fer servir en el disseny d'aquest regulador òptim.
Qualsevol algorisme de construcció concurrent de mapes i autolocalització de robots mòbils que s'ha d'usar en un entorn real ha de ser capaç de relacionar les observacions i els seus corresponents elements del mapa de manera expedita. Algunes de les proves de compatibilitat de les observacions són costoses des del punt de vista de la seva complexitat computacional, i la seva aplicació s'ha de dissenyar amb especial atenció. Es comenten els costos computacionals de les diferents proves de compatibilitat entre observacions; així com altres característiques desitjables de l'estructura de dades que es fa servir per a la construcció del mapa. A més a més es proposen una sèrie de tasques que han de realitzar-se durant l'associació de dades. Començant per les proves de compatibilitat amb un model bàsic dels elements del mapa, i continuant amb la reducció de l'espai de cerca quan es generen hipòtesis d'associació, així com les proves espacial i temporal d'associació de dades.
El treball que es presenta en aquesta tesi proposa noves tècniques en àrees de l'enginyera i ciències computacionals, que van des de nous algorismes per la visió per computador, a idees novells de la construcció concurrent de mapes i l'autolocalització de robots mòbils. Les contribucions principals són la proposta d'una nova tècnica per la fusió de dades visuals; la formulació d'un nou algorisme per la construcció concurrent de mapes i l'autolocalització de robots que considera la qualitat temporal dels elements del mapa; nous resultats teòrics en el nivell de reconstrucció possible quan es construeixen mapes a partir d'observacions totalment correladas; i les tècniques necessàries per pal·liar els efectes de l'observabilitat i la controlabilitat parcials, així com els efectes de les no linealitats en la solució del problema de construcció concurrent de mapes i de l'autolocalització.
Esta tesis aborda el problema del aprendizaje automático de entornos estructurados en robótica móvil. Particularmente, la extracción de características a partir de las se nales de los censores, la construcción autónoma de mapas, y la autolocalización de robots.
Se estudian los fundamentos matemáticos necesarios para la extracción de características a partir de imágenes y registros de un láser, las cuales permiten la identificación unívoca de los elementos del entorno. Los atributos extraídos a partir de la se nal de un solo sensor pueden ser insuficientes a la hora de caracterizar los elementos del entorno de forma invariante; lo que conlleva a la combinación de información de múltiples fuentes. Se presenta un nuevo algoritmo para la fusión de información complementaria extraída de dos módulos de visión de bajo nivel. Esta fusión de información produce descripciones más completas de los objetos presentes en el entorno, los cuales pueden ser seguidos y aprendidos en el contexto de la robótica móvil.
Las variaciones en las condiciones de iluminación y las oclusiones hacen que la asociación de datos en visión por computador sea una tarea difícil de llevar a cabo. Sin embargo, el uso de restricciones geométricas y fotogramétricas permiten reducir la búsqueda de correspondencias entre imágenes; y al centrar la atención en un reducido número de características, estas pueden ser seguidas en imágenes sucesivas, simplificando así el problema de asociación de datos. Se hace hincapié en las técnicas de la geometría de múltiples vistas relevantes para el cómputo de una estimación inicial de la posición de los elementos del entorno, lo cual permite la reconstrucción del movimiento
del robot entre imágenes sucesivas; situación deseable cuando se carece de odometría o cuando sus lecturas son poco fiables.
Una vez que los elementos del entorno han sido extraídos e identificados, la segunda parte del problema consiste en usar estas observaciones tanto para estimar la posición del robot, como para refinar la estimación de los mismos elementos del entorno. El movimiento del robot y las lecturas de los sensores se consideran como dos procesos estocásticos, y el problema se aborda desde el punto de vista de la teoría de estimación, en donde el ruido inherente a los sensores y al movimiento del robot se consideran como secuencias aleatorias.
La principal desventaja existente en el uso de técnicas de estimación para el cómputo concurrente de la posición del robot y la construcción de un mapa, es que hasta ahora se ha considerado su uso en entornos estáticos únicamente, y que su aplicación en situaciones más realistas carece de robustez.
Se propone un conjunto de funciones para evaluar la calidad temporal de las observaciones con el fin de solventar aquellas situaciones en que las observaciones de los elementos del entorno no sean consistentes en el tiempo.
Se muestra como el uso de estas pruebas de calidad temporal junto con las pruebas de compatibilidad espacial existentes mejora los resultados al usar un método de estimación óptima para la construcción concurrente de mapas y la autolocalización de robots. La idea principal consiste en usar un histórico
de los errores en la asociación de datos para el cómputo de la posibilidad de incurrir en nuevos errores de asociación; y eliminar del mapa aquellos elementos cuyas observaciones no sean consistentes.
Se presta especial atención a que la eliminación de elementos inconsistentes del mapa no viole las propiedades de los algoritmos de construcción concurrente de mapas y autolocalización descritos en la literatura; es decir, convergencia asintótica y correlación completa.
Esta tesis proporciona a su vez un análisis en profundidad del modelo de construcción concurrente de mapas y autolocalización totalmente correlado desde un punto de vista de la teoría de control de sistemas. Partiendo del hecho de que el filtro de Kalman no es otra cosa que un estimador óptimo, se analizan las implicaciones de tener un vector de estados que se revisa a partir de mediciones totalmente correladas. Se revela de forma teórica y con experimentos las limitaciones de usar un enfoque para la construcción concurrente de mapas y autolocalización a partir de mediciones totalmente correladas.
El hecho de tener un modelo parcialmente observable inhibe la reconstrucción total del espacio de estados, produciendo a su vez una estimación de la posición de los elementos del entorno que dependerá en todo caso de las observaciones iniciales, y que no garantiza la convergencia a una matriz de covarianza positivamente definida. Por otro lado, el hecho de tener un vector de estados parcialmente controlable, produce después de un reducido número de iteraciones que el filtro crea tener una estimación perfecta del estado de los elementos del entorno; con sus correspondientes ganancias de Kalman convergiendo a cero. Esto es, después de un peque no número de iteraciones del filtro, las innovaciones no se usan. Se muestra como reducir los efectos de la correlación total y la controlabilidad parcial. Además, dado que el filtro de Kalman es un observador óptimo para la reconstrucción de los estados, es pertinente construir un regulador óptimo que permita conducir al robot lo más cerca posible de una trayectoria deseada durante la construcción de un mapa. Se muestra como la dualidad existente entre la observabilidad y la controlabilidad se puede emplear en el diseño de este regulador óptimo.
Cualquier algoritmo de construcción concurrente de mapas y autolocalización de robots móviles que deba funcionar en un entorno real deberá ser capaz de relacionar las observaciones y sus correspondientes elementos del mapa de manera expedita. Algunas de las pruebas de compatibilidad de las observaciones son caras desde el punto de vista de su complejidad computacional, y su aplicación debe diseñarse con riguroso cuidado. Se comentan los costes computacionales de las distintas pruebas de compatibilidad entre observaciones; así como otras características deseadas de la estructura de datos elegida para la construcción del mapa. Además, se propone una serie de tareas que debe llevarse a cabo durante la asociación de datos. Partiendo por las pruebas de compatibilidad con un modelo básico de los elementos del mapa, y continuando con la reducción del espacio de búsqueda al generar hipótesis de asociación, así como las pruebas espacial y temporal de asociación de datos.
El trabajo que se presenta en esta tesis propone nuevas técnicas en áreas de la ingeniería y las ciencias computacionales, que van desde nuevos algoritmos de visión por computador, a ideas noveles en la construcción concurrente de mapas y la autolocalización de robots móviles. Las contribuciones principales son la propuesta de una nueva técnica para la fusión de datos visuales; la formulación de un nuevo algoritmo para la construcción concurrente de mapas y autolocalización de robots que toma en cuenta la calidad temporal de los elementos del mapa; nuevos resultados teóricos en el grado de reconstrucción posible al construir mapas a partir de observaciones totalmente correladas; y las técnicas necesarias para paliar los efectos de la observabilidad y controlabilidad parciales, así como los efectos de las no linealidades en la solución del problema de construcción concurrente de mapas y autolocalización.
This thesis focuses on the various aspects of autonomous environment learning for indoor service robots. Particularly, on landmark extraction from sensor data, autonomous map building, and robot localization.
To univocally identify landmarks from sensor data, we study several landmark representations, and the mathematical foundation necessary to extract the features that build them from images and laser range data. The features extracted from just one sensor may not suce in the invariant characterization of landmarks and objects, pushing for the combination of information from multiple sources. We present a new algorithm that fuses complementary information from two low level vision modules into coherent object models that can be tracked and learned in a mobile robotics context. Illumination conditions and occlusions are the most prominent artifacts
that hinder data association in computer vision. By using photogrammetric and geometric constraints we restrict the search for landmark matches in successive images, and by locking our interest in one or a set of landmarks in the scene, we track those landmarks along successive frames, reducing considerably the data association problem. We concentrate on those tools from the geometry of multiple views that are relevant to the computation of initial landmark location estimates for coarse motion recovery; a desirable characteristic when odometry is not available or is highly unreliable.
Once landmarks are accurately extracted and identied, the second part of the problem is to use these observations for the localization of the robot, as well as the renement of the landmark location estimates. We consider robot motion and sensor observations as stochastic processes, and treat the problem from an estimation theoretic point of view, dealing with noise by using probabilistic methods.
The main drawback we encounter is that current estimation techniques have been devised for static environments, and that they lack robustness in more realistic situations. To aid in those situations in which landmark observations might not be consistent in time, we propose a new set of temporal landmark quality functions, and show how by incorporating these functions in the data association tests, the overall estimation-theoretic approach to map building and localization is improved. The basic idea consists on using the history of data association mismatches for the computation of the likelihood of future data association, together with the spatial compatibility tests already available.
Special attention is paid in that the removal of spurious landmarks from the map does not violate the basic convergence properties of the localization and map building algorithms already described in the literature; namely, asymptotic convergence and full correlation.
The thesis also gives an in depth analysis of the fully correlated model to localization and map building from a control systems theory point of view. Considering the fact that the Kalman .lter is nothing else but an optimal observer, we analyze the implications of having a state vector that is being revised by fully correlated noise measurements. We end up revealing
theoretically and with experiments the strong limitations of using a fully correlated noise driven estimation theoretic approach to map building and localization in relation to the total number of landmarks used.
Partial observability hinders full reconstructibility of the state space, making the .nal map estimate dependant on the initial observations, and does not guarantee convergence to a positive de nite covariance matrix. Partial controllability on the other hand, makes the .lter beleive after a number of iterations, that it has accurate estimates of the landmark states, with their corresponding Kalman gains converging to zero. That is, after a few steps, innovations are useless. We show how to palliate the e.ects of full correlation
and partial controllability. Furthermore, given that the Kalman .lter is an optimal observer for the reconstruction of fully correlated states; it seems pertinent to build an optimal regulator in order to keep the robot as close as possible to a desired motion path when building a map. We show also how the duality between observability and controllability can be exploited in designing such an optimal regulator.
Any map building and localization algorithm for mobile robotics that is to work in real time must be able to relate observations and model matches in an expeditious way. Some of the landmark compatibility tests are computationally expensive, and their application has to be carefully designed. We touch upon the time complexity issues of the various landmark compatibility tests used, and also on the desirable properties of our chosen map data structure.
Furthermore, we propose a series of tasks that must be handled when dealing with landmark data association. From model compatibility tests, to search space reduction and hypothesis formation, to the actual association of observations and models.
The work presented in this thesis spans several areas of engineering and computer science, from new computer vision algorithms, to novel ideas in mobile robot localization and map building. The key contributions are the proposal of a new technique to fuse visual data; the formulation of new algorithms to concurrent localization and map building that take into account temporal landmark quality; new theoretical results on the degree of reconstruction possible when building maps from fully correlated observations; and the necessary techniques to palliate partial observability, partial controllability, and the nonlinear e.ects when solving the simultaneous localization and map building problem.

Robust localization is a prerequisite for mobile robot autonomy. In many situations the GPS signal is not available and thus an additional localization system is required. A simple approach is to apply localization based on dead reckoning by use of wheel encoders but it results in large estimation errors. With exteroceptive sensors such as a laser range finder natural landmarks in the environment of the robot can be extracted from raw range data. Landmarks are extracted with the Hough transform and a recursive line segment algorithm. By applying data association and Kalman filtering along with process models the landmarks can be used in combination with wheel encoders for estimating the global position of the robot. If several robots can cooperate better position estimates are to be expected because robots can be seen as mobile landmarks and one robot can supervise the movement of another. The centralized Kalman filter presented in this master thesis systematically treats robots and extracted landmarks such that benefits from several robots are utilized. Experiments in different indoor environments with two different robots show that long distances can be traveled while the positional uncertainty is kept low. The benefit from cooperating robots in the sense of reduced positional uncertainty is also shown in an experiment.

Except for localization algorithms a typical autonomous robot task in the form of change detection is solved. The change detection method, which requires robust localization, is aimed to be used for surveillance. The implemented algorithm accounts for measurement- and positional uncertainty when determining whether something in the environment has changed. Consecutive true changes as well as sporadic false changes are detected in an illustrative experiment.

In recent years robots have dramatically improved in functionality, but as a result their designs have also become more complicated. The increase in the complexity of the tasks and the design of the robot result in a challenging and time-consuming robot development process. Sophisticated simulation models, expensive hardware setup, and careful human supervisions are necessary to provide a safe and close-to-real world testbed that helps to draw insights to the actual operation. However, the considerable cost and time for creating well-designed tests and for meeting safety requirements present a barrier to rapid development of complex robot systems. This thesis analyses the robot development process and identifies areas for improvement. Based on the requirements analysis, it proposes that, by applying the concept of Mixed Reality (MR) to robot simulation, it is possible to create a realistic, synthetic environment that enables robot developers to experiment freely and safely. The new simulation approach, named MR simulation, offers the flexibility of creating simulation environments composed of real and virtual objects that seamlessly interact with one another. This enables robot developers to mix virtual objects into the real experimental setup for cost and safety reasons. A generic MR framework is proposed that provides the basis for creating MR simulations. The most novel element of the framework is a behaviour based interaction scheme that formalises interactions between real and virtual objects. To validate the framework, a general purpose MR robot simulator is implemented, and it is accompanied by MR interfaces designed to provide users intuitive views of MR simulations. Notably, markerless Augmented Reality (AR) techniques are integrated for real time visualisation. Through three case study evaluations, the use of MR simulations has been demonstrated to produce results that reliably represent the real world. The thesis provides an insight to how MR simulations can help to minimise resource requirements in an industrial application, and enable efficient testing of a prototype aerial robot system. Findings from an initial user study indicate positive acceptance to the technology, while an observational user study identifies a strong contribution of MR simulation to the later stages of robot development.

This thesis project is about the search and secure problem for mobile robots. The search and secure problem refers to the problem where possible moving intruders have to be detected in a given area with obstacles that are represented as polygons. The solution to this problem is given by deploying robots in a proper way so that no intruder can remain undetected or sneak back to a secured area. An intruder is considered detected when he/she is in the field of view of the robots’ on-board cameras. As a first step, in the algorithm that solves the search and secure problem, the area is divided into triangles. The resulting triangles are then merged in order to form convex polygons. The next step is to abstract the actual regions into a topological graph where each polygon is represented by its centroid and the neighboring polygons are connected by edges. At this point, blocking robots are used to break the loops in the graph and prevent the intruders from escaping from the searchers. Then the number of the searchers is determined and their paths are created. Two solutions are proposed, one that requires more searchers but less time and one that requires the minimum number of searchers but more time. The last step is to create the trajectories that the robots have to follow. The functionality and the efficiency of the algorithm is verified through simulations and the results are visualized using Matlab and the AURES simulator and controller. The demonstration that was held at SAAB facilities in Linköping is also described.

We present two different methods based on visual odometry for pose estimation (x, y, Ө) of a robot. The methods proposed are: one appearance based method that computes similarity measures between consecutive images, and one method that computes visual flow of particular features, i.e. spotlights on ceiling. Both techniques are used to correct the pose (x, y, Ө) of the robot, measuring heading change between consecutive images. A simple Kalman filter, extended Kalman filter and simple averaging filter are used to fuse the estimated heading from visual odometry methods with odometry data from wheel encoders. Both techniques are evaluated on three different datasets of images obtained from a warehouse and the results showed that both methods are able to minimize the drift in heading compare to using wheel odometry only.

This thesis presents a possible inexpensive and simple solution for humanitarian demining in developing countries. It consists of a group of mobile robots that can advance and interact collaboratively with each other in a mine field. A base station controls the group and can map their position with the aid of a long range positioning system, thus, identify the landmine position when one is detected by a robot. A short range positioning system is used within the group to measure the distance separating them from one another and the geometry of the formation. A prototype battery powered mobile robot platform has been developed and tested. Electronic hardware and software was designed and built to allow for low level control of the movements of the vehicle and for wireless communications with a base station. The base station exercises high level control over the mobile robot. A positioning system consisting of a long and a short range positioning system has been designed. The short range positioning system, which uses sonic waves within the audible frequency range, has been implemented and tested. Operating within the audible frequency range reduces the sensory system cost and results in an omni-directional range measuring system. The system provides sub-wavelength precision with an absolute error less than 2 cm for distances from 1 m to 4 m at a 5 KHz frequency.

Thèse (M. Ing.)--École de technologie supérieure, Montréal, 2005.
"Thesis presented to École de technologie supérieure as a partial requirement to obtain a masters in electrical engineering". Bibliogr.: f. [140]-142. Également disponible en version électronique.