Thematische Bibliographien / Autonomous vehicle guidance

Auswahl der wissenschaftlichen Literatur zum Thema „Autonomous vehicle guidance“

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Veröffentlicht am 25. Juli 2024

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Zeitschriftenartikel zum Thema "Autonomous vehicle guidance"

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Roundtree, Karina A., Steven Hattrup, Janani Swaminathan, Nicholas Zerbel, Jeffrey Klow, Vivswan Shitole, Abrar Fallatah, Roli Khanna und Julie A. Adams. „Inclusive Design Guidance: External Autonomous Vehicle Interfaces“. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, Nr. 1 (Dezember 2020): 1054–58. http://dx.doi.org/10.1177/1071181320641253.

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Autonomous vehicles are expected on roads in the near future and need to interact safely with external road users, such as manual motor drivers, cyclists, and pedestrians. The particular needs of the external road users, such as children, adults, older adults, and individuals with visual, auditory, and/or cognitive impairments, will vary greatly and must be considered in order to design effective inclusive interfaces for all users. Current interface designs lack effective communication between an autonomous vehicle and external road users with regard to conveying and understanding the mobility intent of each party. The goal is to provide inclusive design guidance for an external human-vehicle interface that enables effective communication between autonomous vehicles and external road users. Factors related to communicating intent, the external road users, and environmental constraints, were used to inform the design guidance.
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Naeem, W., R. Sutton, S. M. Ahmad und R. S. Burns. „A Review of Guidance Laws Applicable to Unmanned Underwater Vehicles“. Journal of Navigation 56, Nr. 1 (Januar 2003): 15–29. http://dx.doi.org/10.1017/s0373463302002138.

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The main problem in bringing autonomy to any vehicle lies in the design of a suitable guidance law. For truly autonomous operation, the vehicle needs to have a reliable Navigation, Guidance and Control (NGC) system of which the guidance system is the key element that generates suitable trajectories to be followed. In this review paper, various guidance laws found in the literature and their relevance to autonomous underwater vehicles (AUVs) are discussed. Since existing guidance laws for underwater vehicles have emulated from tactical airborne missile systems, a number of approaches for the missile guidance systems are considered. Finally, potential guidance strategies for AUVs are proposed.
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D’Angelo, Vincenzo, Paolo Folino, Marco Lupia, Gianfranco Gagliardi, Gianni Cario, Francesco Cicchello Gaccio und Alessandro Casavola. „A ROS-Based GNC Architecture for Autonomous Surface Vehicle Based on a New Multimission Management Paradigm“. Drones 6, Nr. 12 (27.11.2022): 382. http://dx.doi.org/10.3390/drones6120382.

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This paper presents the design and implementation of BAICal (Intelligent Autonomous Buoy by the University of Calabria), an autonomous surface vehicle (ASV) developed at the Autonomous Systems Lab (LASA) of the Department of Computer Science, Modeling, Electronics, and Systems Engineering (DIMES), University of Calabria. The basic project was born as a research program in marine robotics with multiple applications, either in the sea or in lake/river environments, for data monitoring, search and rescue operations and diver support tasks. Mechanical and hardware designs are discussed by considering a three-degree-of-freedom (3DoF) dynamical model of the vehicle. An extension to the typical guidance, navigation, and control (GNC) software architecture is presented. The software design and the implementation of a manager module (M-GNC architecture) that allows the vehicle to autonomously coordinate missions are described. Indeed, autonomous guidance and movement are only one of several more complex tasks that mobile robots have to perform in a real scenario and that allow a long-term life cycle. Module-based software architecture is developed by using the Robot Operating System (ROS) framework that is suitable for different kinds of autonomous vehicles, such as aerial, ground, surface or underwater drones.
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Wong, Joseph, Goldie Nejat, Robert Fenton und Beno Benhabib. „A neural-network approach to high-precision docking of autonomous vehicles/platforms“. Robotica 25, Nr. 4 (13.02.2007): 479–92. http://dx.doi.org/10.1017/s0263574707003359.

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SUMMARYIn this paper, a Neural-Network- (NN) based guidance methodology is proposed for the high-precision docking of autonomous vehicles/platforms. The novelty of the overall online motion-planning methodology is its applicability to cases that do not allow for the direct proximity measurement of the vehicle's pose (position and orientation). In such instances, a guidance technique that utilizes Line-of-Sight- (LOS) based task-space sensory feedback is needed to minimize the detrimental impact of accumulated systematic motion errors. Herein, the proposed NN-based guidance methodology is implemented during the final stage of the vehicle's motion (i.e., docking). Systematic motion errors, which are accumulated after a long-range motion are reduced iteratively by executing corrective motion commands generated by the NN until the vehicle achieves its desired pose within random noise limits. The proposed guidance methodology was successfully tested via simulations for a 6-dof (degree-of-freedom) vehicle and via experiments for a 3-dof high-precision planar platform.
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Zhou, Yunya, Yang He, Yu Yan, Fang Li, Neng Li, Chaofeng Zhang, Zijian Lu und Zhiyong Yang. „Autonomous charging docking control method for unmanned vehicles based on vision and infrared“. Journal of Physics: Conference Series 2584, Nr. 1 (01.09.2023): 012065. http://dx.doi.org/10.1088/1742-6596/2584/1/012065.

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Abstract Unmanned vehicle charging is part of the autonomous workflow of unmanned vehicles. Most existing unmanned vehicles mostly rely on manual battery change or manual charging, which cannot realize autonomous charging. In order to achieve simpler and safer autonomous charging for unmanned vehicles, this paper proposes a new intelligent unmanned vehicle autonomous charging docking method based on infrared guidance and vision assistance. Firstly, the autonomous charging device and intelligent charging stand for unmanned vehicles are designed, and for the unmanned vehicle, charging is not easy to align and easy to detach when charging. The camber-type electric core and charging adsorption device are designed, respectively, and the autonomous charging docking device is designed. Secondly, in order to ensure the accuracy of the docking between the unmanned vehicle and the intelligent charging stand, the unmanned vehicle autonomous charging method is proposed. The combination method of infrared and vision adjusts the posture of the unmanned vehicle. Finally, a protection method of autonomous charging docking based on ultrasonic ranging of unmanned vehicles is proposed. The communication and ranging modules on the unmanned vehicle and intelligent charging stand are designed to prevent mistouching and obstacle avoidance to ensure the safety of the system. The experiment results show that the docking method of this unmanned vehicle autonomous charging system is accurate, efficient, and safe, which can satisfy the demand for unmanned vehicle autonomous charging.
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Foley, James P., und Michael J. Hudak. „Autonomous Route Guidance System Field Test“. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, Nr. 18 (Oktober 1996): 887–90. http://dx.doi.org/10.1177/154193129604001804.

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Eight vehicles equipped with an autonomous Route Guidance System (RGS) were deployed in two geographical areas for a field test. The RGS provided the driver with turn-by-turn instructions to a selected destination using graphics presented on a monochromatic screen and verbal instructions through a dedicated speaker. Each of 45 participants drove a vehicle for approximately one month and reported their experiences in a post-drive debriefing. The debriefing consisted of both a questionnaire and a structured interview. The emphasis of the field test was to evaluate the driver interface. The results indicated that the participants were generally satisfied with the performance and usefulness of this implementation of a route guidance system. They liked the accuracy of the system and the ease of guidance to destinations. Implications for future system design improvements are discussed.
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Hartley, Ralph, Behrooz Kamgar-Parsi und Cody Narber. „Using Roads for Autonomous Air Vehicle Guidance“. IEEE Transactions on Intelligent Transportation Systems 19, Nr. 12 (Dezember 2018): 3840–49. http://dx.doi.org/10.1109/tits.2018.2799485.

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Baker, Patrick, und Behrooz Kamgar-Parsi. „Using shorelines for autonomous air vehicle guidance“. Computer Vision and Image Understanding 114, Nr. 6 (Juni 2010): 723–29. http://dx.doi.org/10.1016/j.cviu.2010.01.009.

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Kim, Kangsoo, und Tamaki Ura. „Applied Model-Based Analysis and Synthesis for the Dynamics, Guidance, and Control of an Autonomous Undersea Vehicle“. Mathematical Problems in Engineering 2010 (2010): 1–23. http://dx.doi.org/10.1155/2010/149385.

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Model-based analysis and synthesis applied to the dynamics, guidance, and control of an autonomous undersea vehicle are presented. As the dynamic model for describing vehicle motion mathematically, the equations of motion are derived. The stability derivatives in the equations of motion are determined by a simulation-based technique using computational fluid dynamics analysis. The dynamic model is applied to the design of the low-level control systems, offering model-based synthetic approach in dynamics and control applications. As an intelligent navigational strategy for undersea vehicles, we present the optimal guidance in environmental disturbances. The optimal guidance aims at the minimum-time transit of a vehicle in an environmental flow disturbance. In this paper, a newly developed algorithm for obtaining the numerical solution of the optimal guidance law is presented. The algorithm is a globally working procedure deriving the optimal guidance in any deterministic environmental disturbance. As a fail-safe tactic in achieving the optimal navigation in environments of moderate uncertainty, we propose the quasi-optimal guidance. Performances of the optimal and the quasi-optimal guidances are demonstrated by the simulated navigations in a few environmental disturbances.
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Zhang, Zhuoyu, Wangjie Ding, Rundong Wu, Mingwei Lin, Dejun Li und Ri Lin. „Autonomous Underwater Vehicle Cruise Positioning and Docking Guidance Scheme“. Journal of Marine Science and Engineering 12, Nr. 6 (19.06.2024): 1023. http://dx.doi.org/10.3390/jmse12061023.

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The Autonomous Underwater Vehicle (AUV) is capable of autonomously conducting underwater cruising tasks. When combined with docking operations, the AUV can replenish its electric power after long-distance travel, enabling it to achieve long-range autonomous monitoring. This paper proposes a positioning method for the cruising and docking stages of AUVs. Firstly, a vision guidance algorithm based on monocular vision and threshold segmentation is studied to address the issue of regional noise that commonly occurs during underwater docking. A solution for regional noise based on threshold segmentation and proportional circle selection is proposed. Secondly, in order to enhance the positioning accuracy during the cruising stage, a fusion positioning algorithm based on particle filtering is presented, incorporating the Doppler Velocity Log (DVL) and GPS carried by the AUV. In simulation, this algorithm improves positioning accuracy by over 56.0% compared to using individual sensors alone. Finally, experiments for cruising and docking were conducted in Qingjiang, Hubei, China. The effectiveness of both methods is demonstrated, with successful docking achieved in four out of five attempts.
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Dissertationen zum Thema "Autonomous vehicle guidance"

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Adolfsson, Alexander, und Daniel Arrhenius. „Overseeing Intersection System for Autonomous Vehicle Guidance“. Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254219.

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Intersections represents one of the most common accident sites in traffic today. The biggest cause of accidents is obstructed view and subpar communication between vehicles. Since autonomous vehicles rely on sensors that require a direct view intersections are some of the most complex situations. Where the potential for inter vehicular communication exists between modern vehicles, it is absent in the older generation. An overseeing intersection system can fill this function during the transition period to fully autonomous traffic. This project aimed to implement an intersection system to assist autonomous vehicles through a crossroad. The assist system’s objective was to collect and transmit data from cars close to the junction to the autonomous vehicles nearby. The concept was tested in simulations by having models traverse a crossroad to evaluate how it utilised the external information. No persistent conclusion could be made due to insufficient simulation environment and vehicle model control.
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Bergquist, Urban. „Colour Vision and Hue for Autonomous Vehicle Guidance“. Thesis, Linköping University, Linköping University, Computer Vision, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54362.

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We explore the use of colour for interpretation of unstructured off-road scenes. The aim is to extract driveable areas for use in an autonomous off-road vehicle in real-time. The terrain is an unstructured tropical jungle area with vegetation, water and red mud roads.

We show that hue is both robust to changing lighting conditions and an important feature for correctly interpreting this type of scene. We believe that our method also can be deployed in other types of terrain, with minor changes, as long as the terrain is coloured and well saturated.

Only 2D information is processed at the moment, but we aim at extending the method to also treat 3D information, by the use of stereo vision or motion.

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Naeem, Wasif. „Guidance and control of an autonomous underwater vehicle“. Thesis, University of Plymouth, 2004. http://hdl.handle.net/10026.1/2822.

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A cooperative project between the Universities of Plymouth and Cranfield was aimed at designing and developing an autonomous underwater vehicle named Hammerhead. The work presented herein is to formulate an advance guidance and control system and to implement it in the Hammerhead. This involves the description of Hammerhead hardware from a control system perspective. In addition to the control system, an intelligent navigation scheme and a state of the art vision system is also developed. However, the development of these submodules is out of the scope of this thesis. To model an underwater vehicle, the traditional way is to acquire painstaking mathematical models based on laws of physics and then simplify and linearise the models to some operating point. One of the principal novelties of this research is the use of system identification techniques on actual vehicle data obtained from full scale in water experiments. Two new guidance mechanisms have also been formulated for cruising type vehicles. The first is a modification of the proportional navigation guidance for missiles whilst the other is a hybrid law which is a combination of several guidance strategies employed during different phases of the flight. In addition to the modelling process and guidance systems, a number of robust control methodologies have been conceived for Hammerhead. A discrete time linear quadratic Gaussian with loop transfer recovery based autopilot is formulated and integrated with the conventional and more advance guidance laws proposed. A model predictive controller (MPC) has also been devised which is constructed using artificial intelligence techniques such as genetic algorithms (CA) and fuzzy logic. A CA is employed as an online optimization routine whilst fuzzy logic has been exploited as an objective function in an MPC framework. The CA-MPC autopilot has been implemented in Hammerhead in real time and results demonstrate excellent robustness despite the presence of disturbances and ever present modelling uncertainty. To the author's knowledge, this is the first successful application of a CA in real time optimization for controller tuning in the marine sector and thus the thesis makes an extremely novel and useful contribution to control system design in general. The controllers are also integrated with the proposed guidance laws and is also considered to be an invaluable contribution to knowledge. Moreover, the autopilots are used in conjunction with a vision based altitude information sensor and simulation results demonstrate the efficacy of the controllers to cope with uncertain altitude demands.
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Mark, Wannes van der. „Stereo and colour vision techniques for autonomous vehicle guidance“. [S.l : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2007. http://dare.uva.nl/document/47628.

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Magrino, Christopher. „Three dimensional guidance for the NPS autonomous underwater vehicle“. Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/28610.

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Cloutier, Michael John. „Guidance and control system for an Autonomous Underwater Vehicle“. Thesis, Monterey, California. Naval Postgraduate School, 1990. http://hdl.handle.net/10945/30635.

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Approved for public release, distribution is unlimited
The Naval Postgraduate School (NPS) is currently involved in a long-term project to investigate and develop real-time control software, artificial intelligence, computer architecture and control systems theory as they pertain to U.S. Navy autonomous vehicle programs. In support of this goal, the NPS is currently designing and fabricating a testbed autonomous underwater vehicle. This work describes the design, development, and testing of a Guidance Subsystem for this testbed vehicle which uses portions of cubic spirals as the desired path to follow between waypoints. In addition, data translation firmware and real-time software for the control surfaces and main motors is designed, implemented and tested. The process of selecting and implementing an appropriate computer architecture in support of these goals is also discussed and detailed, along with the choice of associated computer hardware and real-time operating system software.
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Pears, Nicholas Edwin. „The low-level guidance of an experimental autonomous vehicle“. Thesis, Durham University, 1989. http://etheses.dur.ac.uk/6731/.

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This thesis describes the data processing and the control that constitutes a method of guidance for an autonomous guided vehicle (AGV) operating in a predefined and structured environment such as a warehouse or factory. A simple battery driven vehicle has been constructed which houses an MC68000 based microcomputer and a number of electronic interface cards. In order to provide a user interface, and in order to integrate the various aspects of the proposed guidance method, a modular software package has been developed. This, along with the research vehicle, has been used to support an experimental approach to the research. The vehicle's guidance method requires a series of concatenated curved and straight imaginary Unes to be passed to the vehicle as a representation of a planned path within its environment. Global position specifications for each line and the associated AGV direction and demand speed for each fine constitute commands which are queued and executed in sequence. In order to execute commands, the AGV is equipped with low level sensors (ultrasonic transducers and optical shaft encoders) which allow it to estimate and correct its global position continually. In addition to a queue of commands, the AGV also has a pre-programmed knowledge of the position of a number of correction boards within its environment. These are simply wooden boards approximately 25cm high and between 2 and 5 metres long with small protrusions ("notches") 4cm deep and 10cm long at regular (Im) intervals along its length. When the AGV passes such a correction board, it can measure its perpendicular distance and orientation relative to that board using two sets of its ultrasonic sensors, one set at the rear of the vehicle near to the drive wheels and one set at the front of the vehicle. Data collected as the vehicle moves parallel to a correction board is digitally filtered and subsequently a least squares line fitting procedure is adopted. As well as improving the reliability and accuracy of orientation and distance measurements relative to the board, this provides the basis for an algorithm with which to detect and measure the position of the protrusions on the correction board. Since measurements in three planar, local coordinates can be made (these are: x, the distance travelled parallel to a correction board; and y,the perpendicular distance relative to a correction board; and Ɵ, the clockwise planar orientation relative to the correction board), global position estimation can be corrected. When position corrections are made, it can be seen that they appear as step disturbances to the control system. This control system has been designed to allow the vehicle to move back onto its imaginary line after a position correction in a critically damped fashion and, in the steady state, to track both linear and curved command segments with minimum error.
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Boulekchour, M. „Robust convex optimisation techniques for autonomous vehicle vision-based navigation“. Thesis, Cranfield University, 2015. http://dspace.lib.cranfield.ac.uk/handle/1826/9412.

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This thesis investigates new convex optimisation techniques for motion and pose estimation. Numerous computer vision problems can be formulated as optimisation problems. These optimisation problems are generally solved via linear techniques using the singular value decomposition or iterative methods under an L2 norm minimisation. Linear techniques have the advantage of offering a closed-form solution that is simple to implement. The quantity being minimised is, however, not geometrically or statistically meaningful. Conversely, L2 algorithms rely on iterative estimation, where a cost function is minimised using algorithms such as Levenberg-Marquardt, Gauss-Newton, gradient descent or conjugate gradient. The cost functions involved are geometrically interpretable and can statistically be optimal under an assumption of Gaussian noise. However, in addition to their sensitivity to initial conditions, these algorithms are often slow and bear a high probability of getting trapped in a local minimum or producing infeasible solutions, even for small noise levels. In light of the above, in this thesis we focus on developing new techniques for finding solutions via a convex optimisation framework that are globally optimal. Presently convex optimisation techniques in motion estimation have revealed enormous advantages. Indeed, convex optimisation ensures getting a global minimum, and the cost function is geometrically meaningful. Moreover, robust optimisation is a recent approach for optimisation under uncertain data. In recent years the need to cope with uncertain data has become especially acute, particularly where real-world applications are concerned. In such circumstances, robust optimisation aims to recover an optimal solution whose feasibility must be guaranteed for any realisation of the uncertain data. Although many researchers avoid uncertainty due to the added complexity in constructing a robust optimisation model and to lack of knowledge as to the nature of these uncertainties, and especially their propagation, in this thesis robust convex optimisation, while estimating the uncertainties at every step is investigated for the motion estimation problem. First, a solution using convex optimisation coupled to the recursive least squares (RLS) algorithm and the robust H filter is developed for motion estimation. In another solution, uncertainties and their propagation are incorporated in a robust L convex optimisation framework for monocular visual motion estimation. In this solution, robust least squares is combined with a second order cone program (SOCP). A technique to improve the accuracy and the robustness of the fundamental matrix is also investigated in this thesis. This technique uses the covariance intersection approach to fuse feature location uncertainties, which leads to more consistent motion estimates. Loop-closure detection is crucial in improving the robustness of navigation algorithms. In practice, after long navigation in an unknown environment, detecting that a vehicle is in a location it has previously visited gives the opportunity to increase the accuracy and consistency of the estimate. In this context, we have developed an efficient appearance-based method for visual loop-closure detection based on the combination of a Gaussian mixture model with the KD-tree data structure. Deploying this technique for loop-closure detection, a robust L convex posegraph optimisation solution for unmanned aerial vehicle (UAVs) monocular motion estimation is introduced as well. In the literature, most proposed solutions formulate the pose-graph optimisation as a least-squares problem by minimising a cost function using iterative methods. In this work, robust convex optimisation under the L norm is adopted, which efficiently corrects the UAV’s pose after loop-closure detection. To round out the work in this thesis, a system for cooperative monocular visual motion estimation with multiple aerial vehicles is proposed. The cooperative motion estimation employs state-of-the-art approaches for optimisation, individual motion estimation and registration. Three-view geometry algorithms in a convex optimisation framework are deployed on board the monocular vision system for each vehicle. In addition, vehicle-to-vehicle relative pose estimation is performed with a novel robust registration solution in a global optimisation framework. In parallel, and as a complementary solution for the relative pose, a robust non-linear H solution is designed as well to fuse measurements from the UAVs’ on-board inertial sensors with the visual estimates. The suggested contributions have been exhaustively evaluated over a number of real-image data experiments in the laboratory using monocular vision systems and range imaging devices. In this thesis, we propose several solutions towards the goal of robust visual motion estimation using convex optimisation. We show that the convex optimisation framework may be extended to include uncertainty information, to achieve robust and optimal solutions. We observed that convex optimisation is a practical and very appealing alternative to linear techniques and iterative methods.
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Jantapremjit, Pakpong. „A guidance-control approach applied to an autonomous underwater vehicle“. Thesis, University of Southampton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.494914.

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Subramanian, Vijay. „Autonomous vehicle guidance using machine vision and laser radar for agricultural applications“. [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0011323.

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Bücher zum Thema "Autonomous vehicle guidance"

1

Miller, Richard Kendall. Survey on autonomous vehicle guidance systems. Madison, GA: Future Technology Surveys, 1989.

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2

Magrino, Christopher. Three dimensional guidance for the NPS autonomous underwater vehicle. Monterey, Calif: Naval Postgraduate School, 1991.

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3

Song, Zhengyu, Dangjun Zhao und Stephan Theil, Hrsg. Autonomous Trajectory Planning and Guidance Control for Launch Vehicles. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0613-0.

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Kapelios, Ioannis. Stability of turning rate guidance and control laws for autonomous vehicles. Monterey, Calif: Naval Postgraduate School, 1992.

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5

Flight Mechanics Symposium (1999 Goddard Space Flight Center). 1999 Flight Mechanics Symposium: Proceedings of a conference sponsored and held at NASA Goddard Space Flight Center, Greenbelt, Maryland, May 18-28, 1999. Washington, DC: National Aeronautics and Space Administration, 1999.

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P, Lynch John, und Goddard Space Flight Center, Hrsg. 1999 Flight mechanics symposium. Greenbelt, Md: The Center, 1999.

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Broggi, Alberto, Gianni Conte, Alessandra Fascioli und Massimo Bertozzi. Automatic Vehicle Guidance: The Experience of the ARGO Autonomous Vehicle. World Scientific Publishing Company, 1999.

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Broggi, Alberto, Gianni Conte, Alessandra Fascioli und Massimo Bertozzi. Automatic Vehicle Guidance: The Experience of the ARGO Autonomous Vehicle. World Scientific Publishing Company, 1999.

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Nejat, Goldie. Guidance-based docking of autonomous vehicles. 2005.

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LAND.TECHNIK 2022. VDI Verlag, 2022. http://dx.doi.org/10.51202/9783181023952.

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INHALT Electrical Agricultural Machines Structuring of electrified agricultural machine systems – Diversity of solutions and analysis methods .....1 GridCON2 – Development of a Cable Drum Vehicle Concept to Power 1MW Fully Electric Agricultural Swarms ..... 11 GridCON Swarm – Development of a Grid Connected Fully Autonomous Agricultural Production System ..... 17 Fully electric Tractor with 1000 kWh battery capacity ..... 23 Soil and Modelling The Integration of a Scientific Soil Compaction Risk Indicator (TERRANIMO) into a Holistic Tractor and Implement Optimization System (CEMOS) .....29 Identification of draft force characteristics for a tillage tine with variable geometry ..... 37 Calibration of soil models within the Discrete Element Method (DEM) ..... 45 Automation and Optimization of Working Speed and Depth in Agricultural Soil Tillage with a Model Predictive Control based on Machine Learning ..... 55 Synchronising machine adjustments of combine harvesters for higher fleet performance ..... 65 A generic approach to bridge the gap between route optimization and motion planning for specific guidance points o...
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Buchteile zum Thema "Autonomous vehicle guidance"

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Hongo, Takero, Hideo Arakawa, Gunji Sugimoto, Koichi Tange und Yuzo Yamamoto. „An Automatic Guidance System of a Self-Controlled Vehicle“. In Autonomous Robot Vehicles, 32–37. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-8997-2_3.

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Kober, Werner, Richard Huber und Ralf Oberfell. „Vehicle Reference Lane Calculation for Autonomous Vehicle Guidance Control“. In Automated Driving, 141–58. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31895-0_6.

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Nwagboso, Christopher O. „Autonomous vehicle guidance using laser range imagery“. In Automotive Sensory Systems, 223–42. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1508-7_11.

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Thomanek, F., und E. D. Dickmanns. „Autonomous road vehicle guidance in normal traffic“. In Recent Developments in Computer Vision, 499–507. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-60793-5_103.

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Jia, Jian, Weifeng Chen und Zixuan Wang. „Aerodynamic Parameter Estimation for Launch Vehicles“. In Autonomous Trajectory Planning and Guidance Control for Launch Vehicles, 201–13. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0613-0_7.

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AbstractAerodynamic force plays an important role in the flight of space launch vehicles. Therefore, obtaining accurate aerodynamic characteristics is the basis and prerequisite for establishing an aerodynamic model and designing a vehicle with excellent characteristics.
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Indiveri, Giacomo, und Paul Verschure. „Autonomous vehicle guidance using analog VLSI neuromorphic sensors“. In Lecture Notes in Computer Science, 811–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0020254.

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Wang, Xiaowei, Feng Zhang, Dongsheng Hu, Rong Chen und Zhengyu Song. „Review, Prospect and Technical Challenge of Launch Vehicle“. In Autonomous Trajectory Planning and Guidance Control for Launch Vehicles, 1–31. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0613-0_1.

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AbstractFollowing six decades of development, the technology of launch vehicle has progressed with respect to the dual action of demand traction and technical promotion, providing increasingly valuable high-tech services for society. Currently, the development of launch vehicle is progressing with respect to stronger capabilities, higher reliability, lowering costs, flexibility, and user convenience. Retrospectively, the global development history of the launch vehicle technology can be roughly categorized into four stages with distinct characteristics of the decades.
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Jenie, Yazdi Ibrahim, Erik-Jan van Kampen und Bart Remes. „Cooperative Autonomous Collision Avoidance System for Unmanned Aerial Vehicle“. In Advances in Aerospace Guidance, Navigation and Control, 387–405. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38253-6_24.

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Liu, ChangBo, und Hao Ding. „Research on Optimal Guidance Law of Autonomous Underwater Vehicle“. In Advances in Mechanical and Electronic Engineering, 503–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31507-7_80.

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Riggs, William. „Local Roadmaps for Autonomous Vehicles: Guidance for High-Impact, Low-Cost Policy Strategies“. In Road Vehicle Automation 8, 49–59. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80063-5_5.

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Konferenzberichte zum Thema "Autonomous vehicle guidance"

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Kyung-Bok Sung, Kyoung-Wook Min, Ju-Wan Kim und Jung-Dan Choi. „Autonomous vehicle guidance system with infrastructure“. In 2013 7th International Conference on Signal Processing and Communication Systems (ICSPCS). IEEE, 2013. http://dx.doi.org/10.1109/icspcs.2013.6723936.

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Salehi, Amir, Jinbiao Li und Ping Lu. „Motion controller design of autonomous vehicle“. In Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-3345.

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Ryoo, Young-Jae, Young-Hak Chang, Dae-Yeong Lim und Yong-Jun Lee. „Autonomous Robotic Vehicle (Robicle) With Ambient Intelligence“. In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86986.

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Magnetic sensing is a reliable technology that has been developed for the purposed of position measurement and guidance, especially for applications in autonomous robotic vehicles. To calculate a position of a magnetic guidance road, it should be estimated in real-time. While the capability of a microprocessor and memory spaces have the limitation in implementation. To solve the above problems, this paper proposes a new structure of the magnetic sensors included a vertical magnetic field. The proposed method uses the linear region of the sensor output, and position determination using a simple equation with a microcontroller. The position sensing technique was implemented in the guidance of autonomous vehicle. The test results show that position sensing can be useful for an autonomous robotic vehicle.
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Gadhvi, Tirth, und Praveen Shankar. „Autonomous Vehicle Guidance Using Neural Network and Random Forest Model“. In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-113414.

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Abstract In this paper, a guidance strategy for autonomous vehicles aimed at preventing collisions caused by faulty sensor data is presented. A kinematic bicycle model is utilized to generate a vehicle motion dataset for training the prediction models. The algorithm employs a random forest prediction model, utilizing a neural network generated dataset to minimize errors in planning the motion. As a case study for implementing the guidance algorithm, a freeway entrance ramp scenario was simulated utilizing MATLAB. The guidance strategy addresses the limitations of GPS-based autonomous vehicle navigation systems, which may experience inaccuracies due to atmospheric conditions and other factors, thereby preventing collisions under such conditions of error.
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Boudali, Mohamed, Rodolfo Orjuela, Michel Basset und Rachid Attia. „Emergency Autonomous Vehicle Guidance Under Steering Loss“. In 2018 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2018. http://dx.doi.org/10.1109/ivs.2018.8500539.

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Beyer, James, Charles Jacobus und Frank Pont. „Autonomous Vehicle Guidance Using Laser Range Imagery“. In Robotics and IECON '87 Conferences, herausgegeben von Wendell H. Chun und William J. Wolfe. SPIE, 1987. http://dx.doi.org/10.1117/12.968234.

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Lazarus, Samuel, Antonios Tsourdos, Nabil Aouf, Rafal Zbikowski und Brian White. „Autonomous Aerial Vehicle Localisation and Mapping“. In AIAA Guidance, Navigation and Control Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2007. http://dx.doi.org/10.2514/6.2007-6792.

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Sousa, Jose P., Bruno M. Ferreira und Nuno A. Cruz. „Guidance of an Autonomous Surface Vehicle for Underwater Navigation Aid“. In 2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV). IEEE, 2018. http://dx.doi.org/10.1109/auv.2018.8729815.

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Richards, Arthur, und Patrick Boyle. „Combining Planning and Learning for Autonomous Vehicle Navigation“. In AIAA Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-7866.

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Mysliwetz, Birger D., und E. D. Dickmanns. „Distributed Scene Analysis For Autonomous Road Vehicle Guidance“. In Robotics and IECON '87 Conferences, herausgegeben von Wendell H. Chun und William J. Wolfe. SPIE, 1987. http://dx.doi.org/10.1117/12.968237.

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Berichte der Organisationen zum Thema "Autonomous vehicle guidance"

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Ukkusuri, Satish, Fasil Sagir, Nishtha Mahajan, Benjamin Bowman und Salil Sharma. Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future. Purdue University, August 2019. http://dx.doi.org/10.5703/1288284316879.

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Dukarski, Jennifer. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles. SAE International, September 2021. http://dx.doi.org/10.4271/epr2021019.

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Modern automobiles collect around 25 gigabytes of data per hour and autonomous vehicles are expected to generate more than 100 times that number. In comparison, the Apollo Guidance Computer assisting in the moon launches had only a 32-kilobtye hard disk. Without question, the breadth of in-vehicle data has opened new possibilities and challenges. The potential for accessing this data has led many entrepreneurs to claim that data is more valuable than even the vehicle itself. These intrepid data-miners seek to explore business opportunities in predictive maintenance, pay-as-you-drive features, and infrastructure services. Yet, the use of data comes with inherent challenges: accessibility, ownership, security, and privacy. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles examines some of the pressing questions on the minds of both industry and consumers. Who owns the data and how can it be used? What are the regulatory regimes that impact vehicular data use? Is the US close to harmonizing with other nations in the automotive data privacy? And will the risks of hackers lead to the “zombie car apocalypse” or to another avenue for ransomware? This report explores a number of these legal challenges and the unsettled aspects that arise in the world of automotive data
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Cowen, Steve, Susan Briest und James Dombrowski. Underwater Docking of Autonomous Undersea Vehicles Using Optical Terminal Guidance. Fort Belvoir, VA: Defense Technical Information Center, Oktober 1997. http://dx.doi.org/10.21236/ada422445.

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Benkraouda, Ouafa, Lindsay Braun und Arnab Chakraborty. Policies and Design Guidelines to Plan for Connected and Autonomous Vehicles. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-012.

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This report chronicles the work undertaken by researchers at the University of Illinois Urbana Champaign to identify policies and design guidelines to plan for connected and autonomous vehicles (CAVs) in mid-sized regions in Illinois. The report starts with the goals of this work followed by a review of existing literature. The review addresses CAV technologies and scenario planning, including academic research articles, policies and guidance documents from federal and state agencies, and recent long-range transportation plans. The review findings are organized into three categories—drivers, levers, and impacts—to facilitate scenario-based planning and included key factors and trends in technology development and adoption (drivers), mechanisms that planners and policymakers may employ to intervene in or prepare for CAV futures (levers), and community-level outcomes of different plausible CAV futures (impacts). Primary research was undertaken first by interviewing practitioners in six mid-sized regions of Illinois to collect inputs about their needs and obstacles to planning for CAVs, as well as to understand their sense of their community’s preparedness for CAVs. The research team then conducted a detailed survey of over 700 residents from the Greater Peoria region to understand their would-be travel behavior and residential location decisions in a CAV future and general attitude toward self-driving cars. These inputs helped identify the key drivers, levers, and impacts to be employed in creating scenarios, a list of selected policies and design, and a framework to select appropriate responses based on the needs and desires of a community. The detailed scenarios are as follows: (1) continuation of the status quo, (2) private multimodal future, and (3) shared multimodal future. The policies and design guidelines are identified for each scenario and are categorized into six sets of action items: general, data and digitization, mobility and traffic, street design, infrastructure, and planning. Specific details of each action item are organized in a format that allows the user to consider each item carefully and to assess its feasibility in a specific region or city. The appendices include background documents related to primary research and, importantly, a handbook for practitioners.
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