Download or read book Optimal Motion Planning for Multiple Point Robots in the Plane written by Erik Lanny Wynters and published by . This book was released on 1991 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multi robot Optimal Motion Planning written by Guoxiang Zhao and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent rapid development of computing, communication and sensing technologies triggers the prevalence of multi-robot systems. Compared to single-robot systems, multi-robot systems are advantageous in three aspects: 1) they can accomplish tasks which are beyond the capabilities of single robots; 2) they are cheaper and more flexible for certain tasks; 3) control scheme of multi-robot systems may reveal insights into key issues in social and life sciences. Multi-robot systems have numerous applications in various areas, such as traffic coordination and precision agriculture. Robotic motion planning is a fundamental problem where a sequence of controls are identified to steer robots to goal regions subject to geometric and dynamic constraints. However, the problem is computationally hard even for a single robot. The generalized mover's problem is shown to be PSPACE-hard in degrees of freedom. The optimal motion planning, where the aggregate cost along the returned trajectory is minimized, is more computationally challenging. It is shown that computing the shortest path in R^3 populated with obstacles is NP-hard in the number of obstacles. Multi-robot motion planning is even harder than its single-robot counterpart and its worst-case computational complexity grows exponentially in the number of robots. In this dissertation, we aim to study multi-robot optimal motion planning and design a set of planners towards scalability and optimality. Our research is three-fold. We first investigate the scenario where a team of robots desire to arrive at their own goal regions as soon as possible. The robots are governed by complex dynamics and need to maintain safe distance from static obstacles and other robots. The optimality of the solution is characterized by Pareto optimality, where the reduction of one robot's travelling time must cause the rise of others'. A novel numerical algorithm is proposed to identify the Pareto optimal solutions where no robot can unilaterally reduce its traveling time without extending others'. The consistent approximation of the algorithm in the epigraphical profile sense is guaranteed using set-valued numerical analysis. Experiments on an indoor multi-robot platform and computer simulations show the anytime property of the proposed algorithm; i.e., it is able to quickly return a feasible control policy that safely steers the robots to their goal regions and it keeps improving policy optimality if more time is given. Then we propose a distributed algorithm to achieve much better scalability. Specifically, the algorithm integrates decoupled optimal feedback planning and distributed conflict resolution to coordinate a fleet of unicycle robots. Each robot independently generates its optimal motions offline and avoids collisions with other objects in online execution. The computational complexity is independent of the robot number. Moreover, each robot's individual planner is optimal and its motion is rarely interfered in exercise, so the algorithm is near-optimal. Collision avoidance and finite-time arrival at the goal regions are formally guaranteed. A set of simulations are conducted to verify the scalability and near-optimality of the proposed algorithm. Lastly, we propose a distributed optimal motion planning algorithm for heterogeneous multi-robot systems and strongly coupled missions to balance scalability and optimality, where multiple robots of different dynamics desire to safely reach their respective goal regions with minimal cost. Each robot shares its policy with others in parallel and takes best response with respect to others' policies in a sequential fashion. The proposed algorithm is shown to converge to the optimal value function, and the computational complexity is linear with respect to robot number but is much smaller than benchmark. A set of simulations are conducted to verify the scalability and near-optimality of the proposed algorithm.
Download or read book Modern Robotics written by Kevin M. Lynch and published by Cambridge University Press. This book was released on 2017-05-25 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern and unified treatment of the mechanics, planning, and control of robots, suitable for a first course in robotics.
Download or read book Optimized Motion Planning written by Cherif Ahrikencheikh and published by Wiley-Interscience. This book was released on 1994-10-14 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first handbook to the practical specifics of motion planning, Optimized-Motion Planning offers design engineers methods and insights for solving real motion planning problems in a 3-dimensional space. Complete with a disk of software programs, this unique guide allows users to design, test, and implement possible solutions, useful in a host of contexts, especially tool path planning. Beginning with a brief overview of the general class of problems examined within the book as well as available solution techniques, Part 1 familiarizes the reader with the conceptual threads that underlie each approach. This early discussion also considers the specific applications of each technique as well as its computational efficiency. Part 2 illustrates basic problem-solving methodology by considering the case of a point moving between stationary polygons in a plane. This section features algorithms for data organization and storage, the concepts of passage networks and feasibility charts, as well as the path optimization algorithm. Elaborating on the problematic model described in Part 2, Part 3 develops an algorithm for optimizing the motion of a point between stationary polyhedra in a 3-dimensional space. This algorithm is first applied to the case of nonpoint objects moving between obstacles that can be stationary or moving with known patterns. It's then used in connection with the extensively investigated problem of motion planning for multilink manipulators.
Download or read book Robot Motion Planning and Control written by Jean-Paul Laumond and published by Springer. This book was released on 1998 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content Description #Includes bibliographical references.
Download or read book Motion Planning of Multi robot System for Airplane Stripping written by Rawan Kalawoun and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This PHD is a part of a French project named AEROSTRIP, (a partnership between Pascal Institute,Sigma, SAPPI, and Air-France industries), it is funded by the French Government through the FUIProgram (20th call). The AEROSTRIP project aims at developing the first automated system thatecologically cleans the airplanes surfaces using a process of soft projection of ecological media onthe surface (corn). My PHD aims at optimizing the trajectory of the whole robotic systems in orderto optimally strip the airplane. Since a large surface can not be totally covered by a single robot base placement, repositioning of the robots is necessary to ensure a complete stripping of the surface. The goal in this work is to find the optimal number of robots with their optimal positions required to totally strip the air-plane. Once found, we search for the trajectories of the robots of the multi-robot system between those poses. Hence, we define a general framework to solve this problem having four main steps: the pre-processing step, the optimization algorithm step, the generation of the end-effector trajectories step and the robot scheduling, assignment and control step.In my thesis, I present two contributions in two different steps of the general framework: the pre-processing step, the optimization algorithm step. The computation of the robot workspace is required in the pre-processing step: we proposed Interval Analysis to find this workspace since it guarantees finding solutions in a reasonable computation time. Though, our first contribution is a new inclusion function that reduces the pessimism, the overestimation of the solution, which is the main disadvantage of Interval Analysis. The proposed inclusion function is assessed on some Constraints Satisfaction Problems and Constraints Optimization problems. Furthermore, we propose an hybrid optimization algorithm in order to find the optimal number of robots with their optimal poses: it is our second contribution in the optimization algorithm step. To assess our hybrid optimization algorithm, we test the algorithm on regular surfaces, such as a cylinder and a hemisphere, and on a complex surface: a car.
Download or read book Computational Geometry for Multiple robot Motion Planning written by Susan Elizabeth Hert and published by . This book was released on 1997 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Complexity of Robot Motion Planning written by John Canny and published by MIT Press. This book was released on 1988 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Complexity of Robot Motion Planning makes original contributions both to roboticsand to the analysis of algorithms. In this groundbreaking monograph John Canny resolveslong-standing problems concerning the complexity of motion planning and, for the central problem offinding a collision free path for a jointed robot in the presence of obstacles, obtains exponentialspeedups over existing algorithms by applying high-powered new mathematical techniques.Canny's newalgorithm for this "generalized movers' problem," the most-studied and basic robot motion planningproblem, has a single exponential running time, and is polynomial for any given robot. The algorithmhas an optimal running time exponent and is based on the notion of roadmaps - one-dimensionalsubsets of the robot's configuration space. In deriving the single exponential bound, Cannyintroduces and reveals the power of two tools that have not been previously used in geometricalgorithms: the generalized (multivariable) resultant for a system of polynomials and Whitney'snotion of stratified sets. He has also developed a novel representation of object orientation basedon unnormalized quaternions which reduces the complexity of the algorithms and enhances theirpractical applicability.After dealing with the movers' problem, the book next attacks and derivesseveral lower bounds on extensions of the problem: finding the shortest path among polyhedralobstacles, planning with velocity limits, and compliant motion planning with uncertainty. Itintroduces a clever technique, "path encoding," that allows a proof of NP-hardness for the first twoproblems and then shows that the general form of compliant motion planning, a problem that is thefocus of a great deal of recent work in robotics, is non-deterministic exponential time hard. Cannyproves this result using a highly original construction.John Canny received his doctorate from MITAnd is an assistant professor in the Computer Science Division at the University of California,Berkeley. The Complexity of Robot Motion Planning is the winner of the 1987 ACM DoctoralDissertation Award.
Download or read book Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments written by Kristoffer Bergman and published by Linköping University Electronic Press. This book was released on 2021-03-16 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. The objective in optimal motion planning problems is to find feasible motion plans that also optimize a performance measure. From a control perspective, the problem is an instance of an optimal control problem. This thesis addresses optimal motion planning problems for complex dynamical systems that operate in unstructured environments, where no prior reference such as road-lane information is available. Some example scenarios are autonomous docking of vessels in harbors and autonomous parking of self-driving tractor-trailer vehicles at loading sites. The focus is to develop optimal motion planning algorithms that can reliably be applied to these types of problems. This is achieved by combining recent ideas from automatic control, numerical optimization and robotics. The first contribution is a systematic approach for computing local solutions to motion planning problems in challenging unstructured environments. The solutions are computed by combining homotopy methods and direct optimal control techniques. The general principle is to define a homotopy that transforms, or preferably relaxes, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments, where the presented method outperforms a state-of-the-art asymptotically optimal motion planner based on random sampling. The second contribution is an optimization-based framework for automatic generation of motion primitives for lattice-based motion planners. Given a family of systems, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance, the framework computes a library of motion primitives by simultaneously optimizing the motions and the terminal states. The final contribution of this thesis is a motion planning framework that combines the strengths of sampling-based planners with direct optimal control in a novel way. The sampling-based planner is applied to the problem in a first step using a discretized search space, where the system dynamics and objective function are chosen to coincide with those used in a second step based on optimal control. This combination ensures that the sampling-based motion planner provides a feasible motion plan which is highly suitable as warm-start to the optimal control step. Furthermore, the second step is modified such that it also can be applied in a receding-horizon fashion, where the proposed combination of methods is used to provide theoretical guarantees in terms of recursive feasibility, worst-case objective function value and convergence to the terminal state. The proposed motion planning framework is successfully applied to several problems in challenging unstructured environments for tractor-trailer vehicles. The framework is also applied and tailored for maritime navigation for vessels in archipelagos and harbors, where it is able to compute energy-efficient trajectories which complies with the international regulations for preventing collisions at sea.
Download or read book Motion Planning for Dynamic Agents written by Zain Anwar Ali and published by BoD – Books on Demand. This book was released on 2024-01-17 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, Motion Planning for Dynamic Agents, presents a thorough overview of current advancements and provides insights into the fascinating and vital field of aeronautics. It focuses on modern research and development, with an emphasis on dynamic agents. The chapters address a wide range of complex capabilities, including formation control, guidance and navigation, control techniques, wide-space coverage for inspection and exploration, and the best pathfinding in unknown territory. This book is a valuable resource for scholars, practitioners, and amateurs alike due to the variety of perspectives that are included, which help readers gain a sophisticated understanding of the difficulties and developments in the area of study.
Download or read book Algorithmic Foundations of Robotics V written by Jean-Daniel Boissonnat and published by Springer Science & Business Media. This book was released on 2003-09-11 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Selected contributions to the Workshop WAFR 2002, held December 15-17, 2002, Nice, France. This fifth biannual Workshop on Algorithmic Foundations of Robotics focuses on algorithmic issues related to robotics and automation. The design and analysis of robot algorithms raises fundamental questions in computer science, computational geometry, mechanical modeling, operations research, control theory, and associated fields. The highly selective program highlights significant new results such as algorithmic models and complexity bounds. The validation of algorithms, design concepts, or techniques is the common thread running through this focused collection.
Download or read book Principles of Robot Motion written by Howie Choset and published by MIT Press. This book was released on 2005-05-20 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts. Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on circuit boards, directing digital actors in computer graphics, robot-assisted surgery and medicine, and in novel areas such as drug design and protein folding. This text reflects the great advances that have taken place in the last ten years, including sensor-based planning, probabalistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, rleating low-level implementation details to high-level algorithmic concepts.
Download or read book Motion Planning in Dynamic Environments written by Kikuo Fujimura and published by Springer. This book was released on 1991 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Planning Algorithms written by Steven M. LaValle and published by Cambridge University Press. This book was released on 2006-05-29 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.
Download or read book Nonholonomic Motion Planning written by Zexiang Li and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonholonomic Motion Planning grew out of the workshop that took place at the 1991 IEEE International Conference on Robotics and Automation. It consists of contributed chapters representing new developments in this area. Contributors to the book include robotics engineers, nonlinear control experts, differential geometers and applied mathematicians. Nonholonomic Motion Planning is arranged into three chapter groups: Controllability: one of the key mathematical tools needed to study nonholonomic motion. Motion Planning for Mobile Robots: in this section the papers are focused on problems with nonholonomic velocity constraints as well as constraints on the generalized coordinates. Falling Cats, Space Robots and Gauge Theory: there are numerous connections to be made between symplectic geometry techniques for the study of holonomies in mechanics, gauge theory and control. In this section these connections are discussed using the backdrop of examples drawn from space robots and falling cats reorienting themselves. Nonholonomic Motion Planning can be used either as a reference for researchers working in the areas of robotics, nonlinear control and differential geometry, or as a textbook for a graduate level robotics or nonlinear control course.
Download or read book Repetitive Motion Planning and Control of Redundant Robot Manipulators written by Yunong Zhang and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Repetitive Motion Planning and Control of Redundant Robot Manipulators presents four typical motion planning schemes based on optimization techniques, including the fundamental RMP scheme and its extensions. These schemes are unified as quadratic programs (QPs), which are solved by neural networks or numerical algorithms. The RMP schemes are demonstrated effectively by the simulation results based on various robotic models; the experiments applying the fundamental RMP scheme to a physical robot manipulator are also presented. As the schemes and the corresponding solvers presented in the book have solved the non-repetitive motion problems existing in redundant robot manipulators, it is of particular use in applying theoretical research based on the quadratic program for redundant robot manipulators in industrial situations. This book will be a valuable reference work for engineers, researchers, advanced undergraduate and graduate students in robotics fields. Yunong Zhang is a professor at The School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China; Zhijun Zhang is a research fellow working at the same institute.
Download or read book On Motion Planning Using Numerical Optimal Control written by Kristoffer Bergman and published by Linköping University Electronic Press. This book was released on 2019-05-28 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. In this thesis, the objective is not only to find feasible solutions to a motion planning problem, but solutions that also optimize some kind of performance measure. From a control perspective, the resulting problem is an instance of an optimal control problem. In this thesis, the focus is to further develop optimal control algorithms such that they be can used to obtain improved solutions to motion planning problems. This is achieved by combining ideas from automatic control, numerical optimization and robotics. First, a systematic approach for computing local solutions to motion planning problems in challenging environments is presented. The solutions are computed by combining homotopy methods and numerical optimal control techniques. The general principle is to define a homotopy that transforms, or preferably relaxes, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments, where the presented method outperforms both a state-of-the-art numerical optimal control method based on standard initialization strategies and a state-of-the-art optimizing sampling-based planner based on random sampling. Second, a framework for automatically generating motion primitives for lattice-based motion planners is proposed. Given a family of systems, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance, the algorithm not only automatically optimizes the motions connecting pre-defined boundary conditions, but also simultaneously optimizes the terminal state constraints as well. In addition to handling static a priori known system parameters such as platform dimensions, the framework also allows for fast automatic re-optimization of motion primitives if the system parameters change while the system is in use. Furthermore, the proposed framework is extended to also allow for an optimization of discretization parameters, that are are used by the lattice-based motion planner to define a state-space discretization. This enables an optimized selection of these parameters for a specific system instance. Finally, a unified optimization-based path planning approach to efficiently compute locally optimal solutions to advanced path planning problems is presented. The main idea is to combine the strengths of sampling-based path planners and numerical optimal control. The lattice-based path planner is applied to the problem in a first step using a discretized search space, where system dynamics and objective function are chosen to coincide with those used in a second numerical optimal control step. This novel tight combination of a sampling-based path planner and numerical optimal control makes, in a structured way, benefit of the former method’s ability to solve combinatorial parts of the problem and the latter method’s ability to obtain locally optimal solutions not constrained to a discretized search space. The proposed approach is shown in several practically relevant path planning problems to provide improvements in terms of computation time, numerical reliability, and objective function value.
