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Book Multi robot Optimal Motion Planning

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.

Book Artificial Intelligence and Soft Computing

Download or read book Artificial Intelligence and Soft Computing written by Amit Konar and published by CRC Press. This book was released on 2018-10-08 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: With all the material available in the field of artificial intelligence (AI) and soft computing-texts, monographs, and journal articles-there remains a serious gap in the literature. Until now, there has been no comprehensive resource accessible to a broad audience yet containing a depth and breadth of information that enables the reader to fully understand and readily apply AI and soft computing concepts. Artificial Intelligence and Soft Computing fills this gap. It presents both the traditional and the modern aspects of AI and soft computing in a clear, insightful, and highly comprehensive style. It provides an in-depth analysis of mathematical models and algorithms and demonstrates their applications in real world problems. Beginning with the behavioral perspective of "human cognition," the text covers the tools and techniques required for its intelligent realization on machines. The author addresses the classical aspects-search, symbolic logic, planning, and machine learning-in detail and includes the latest research in these areas. He introduces the modern aspects of soft computing from first principles and discusses them in a manner that enables a beginner to grasp the subject. He also covers a number of other leading aspects of AI research, including nonmonotonic and spatio-temporal reasoning, knowledge acquisition, and much more. Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain is unique for its diverse content, clear presentation, and overall completeness. It provides a practical, detailed introduction that will prove valuable to computer science practitioners and students as well as to researchers migrating to the subject from other disciplines.

Book Robot Motion Planning and Control

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.

Book Autonomous Mobile Robots and Multi Robot Systems

Download or read book Autonomous Mobile Robots and Multi Robot Systems written by Eugene Kagan and published by John Wiley & Sons. This book was released on 2019-12-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a theoretical and practical guide to the communication and navigation of autonomous mobile robots and multi-robot systems This book covers the methods and algorithms for the navigation, motion planning, and control of mobile robots acting individually and in groups. It addresses methods of positioning in global and local coordinates systems, off-line and on-line path-planning, sensing and sensors fusion, algorithms of obstacle avoidance, swarming techniques and cooperative behavior. The book includes ready-to-use algorithms, numerical examples and simulations, which can be directly implemented in both simple and advanced mobile robots, and is accompanied by a website hosting codes, videos, and PowerPoint slides Autonomous Mobile Robots and Multi-Robot Systems: Motion-Planning, Communication and Swarming consists of four main parts. The first looks at the models and algorithms of navigation and motion planning in global coordinates systems with complete information about the robot’s location and velocity. The second part considers the motion of the robots in the potential field, which is defined by the environmental states of the robot's expectations and knowledge. The robot's motion in the unknown environments and the corresponding tasks of environment mapping using sensed information is covered in the third part. The fourth part deals with the multi-robot systems and swarm dynamics in two and three dimensions. Provides a self-contained, theoretical guide to understanding mobile robot control and navigation Features implementable algorithms, numerical examples, and simulations Includes coverage of models of motion in global and local coordinates systems with and without direct communication between the robots Supplemented by a companion website offering codes, videos, and PowerPoint slides Autonomous Mobile Robots and Multi-Robot Systems: Motion-Planning, Communication and Swarming is an excellent tool for researchers, lecturers, senior undergraduate and graduate students, and engineers dealing with mobile robots and related issues.

Book Handbook of Discrete and Computational Geometry

Download or read book Handbook of Discrete and Computational Geometry written by Csaba D. Toth and published by CRC Press. This book was released on 2017-11-22 with total page 2354 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Discrete and Computational Geometry is intended as a reference book fully accessible to nonspecialists as well as specialists, covering all major aspects of both fields. The book offers the most important results and methods in discrete and computational geometry to those who use them in their work, both in the academic world—as researchers in mathematics and computer science—and in the professional world—as practitioners in fields as diverse as operations research, molecular biology, and robotics. Discrete geometry has contributed significantly to the growth of discrete mathematics in recent years. This has been fueled partly by the advent of powerful computers and by the recent explosion of activity in the relatively young field of computational geometry. This synthesis between discrete and computational geometry lies at the heart of this Handbook. A growing list of application fields includes combinatorial optimization, computer-aided design, computer graphics, crystallography, data analysis, error-correcting codes, geographic information systems, motion planning, operations research, pattern recognition, robotics, solid modeling, and tomography.

Book Algorithmic Foundations of Robotics X

Download or read book Algorithmic Foundations of Robotics X written by Emilio Frazzoli and published by Springer. This book was released on 2013-02-14 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are a fundamental component of robotic systems. Robot algorithms process inputs from sensors that provide noisy and partial data, build geometric and physical models of the world, plan high-and low-level actions at different time horizons, and execute these actions on actuators with limited precision. The design and analysis of robot algorithms raise a unique combination of questions from many elds, including control theory, computational geometry and topology, geometrical and physical modeling, reasoning under uncertainty, probabilistic algorithms, game theory, and theoretical computer science. The Workshop on Algorithmic Foundations of Robotics (WAFR) is a single-track meeting of leading researchers in the eld of robot algorithms. Since its inception in 1994, WAFR has been held every other year, and has provided one of the premiere venues for the publication of some of the eld's most important and lasting contributions. This books contains the proceedings of the tenth WAFR, held on June 13{15 2012 at the Massachusetts Institute of Technology. The 37 papers included in this book cover a broad range of topics, from fundamental theoretical issues in robot motion planning, control, and perception, to novel applications.

Book Robot Path Planning and Cooperation

Download or read book Robot Path Planning and Cooperation written by Anis Koubaa and published by Springer. This book was released on 2018-04-05 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents extensive research on two main problems in robotics: the path planning problem and the multi-robot task allocation problem. It is the first book to provide a comprehensive solution for using these techniques in large-scale environments containing randomly scattered obstacles. The research conducted resulted in tangible results both in theory and in practice. For path planning, new algorithms for large-scale problems are devised and implemented and integrated into the Robot Operating System (ROS). The book also discusses the parallelism advantage of cloud computing techniques to solve the path planning problem, and, for multi-robot task allocation, it addresses the task assignment problem and the multiple traveling salesman problem for mobile robots applications. In addition, four new algorithms have been devised to investigate the cooperation issues with extensive simulations and comparative performance evaluation. The algorithms are implemented and simulated in MATLAB and Webots.

Book Motion Planning for Dynamic Agents

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.

Book The Complexity of Robot Motion Planning

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.

Book ICT Innovations 2013

Download or read book ICT Innovations 2013 written by Vladimir Trajkovik and published by Springer Science & Business Media. This book was released on 2013-07-20 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information communication technologies have become the necessity in everyday life enabling increased level of communication, processing and information exchange to extent that one could not imagine only a decade ago. Innovations in these technologies open new fields in areas such as: language processing, biology, medicine, robotics, security, urban planning, networking, governance and many others. The applications of these innovations are used to define services that not only ease, but also increase the quality of life. Good education is essential for establishing solid basis of individual development and performance. ICT is integrated part of education at every level and type. Therefore, the special focus should be given to possible deployment of the novel technologies in order to achieve educational paradigms adapted to possible educational consumer specific and individual needs. This book offers a collection of papers presented at the Fifth International Conference on ICT Innovations held in September 2013, in Ohrid, Macedonia. The conference gathered academics, professionals and practitioners in developing solutions and systems in the industrial and business arena especially innovative commercial implementations, novel applications of technology, and experience in applying recent ICT research advances to practical solutions.

Book Modern Robotics

    Book Details:
  • Author : Kevin M. Lynch
  • Publisher : Cambridge University Press
  • Release : 2017-05-25
  • ISBN : 1107156300
  • Pages : 545 pages

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.

Book Multi Robot Systems

    Book Details:
  • Author : Toshiyuki Yasuda
  • Publisher : BoD – Books on Demand
  • Release : 2011-01-30
  • ISBN : 9533074256
  • Pages : 600 pages

Download or read book Multi Robot Systems written by Toshiyuki Yasuda and published by BoD – Books on Demand. This book was released on 2011-01-30 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of 29 excellent works and comprised of three sections: task oriented approach, bio inspired approach, and modeling/design. In the first section, applications on formation, localization/mapping, and planning are introduced. The second section is on behavior-based approach by means of artificial intelligence techniques. The last section includes research articles on development of architectures and control systems.

Book Generative Multi robot Task and Motion Planning Over Long Horizons

Download or read book Generative Multi robot Task and Motion Planning Over Long Horizons written by Enrique Fernández González (Ph. D.) and published by . This book was released on 2018 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: The state of the art practice in robotics planning is to script behaviors manually, where each behavior is typically precomputed in advance. However, in order for robots to be able to act robustly and adapt to novel situations, they need to be able to plan sequences of behaviors and activities autonomously. Since the conditions and effects of these behaviors are tightly coupled through time, state and control variables, many problems require that the tasks of activity planning and trajectory optimization are considered together. There are two key issues underlying effective hybrid activity and trajectory planning: the sufficiently accurate modeling of robot dynamics and the capability of planning over long horizons. Hybrid activity and trajectory planners that employ mixed integer programming within a discrete time formulation are able to accurately model complex dynamics for robot vehicles, but are often restricted to relatively short horizons. On the other hand, current hybrid activity planners that employ continuous time formulations can handle longer horizons but they only allow actions to have continuous effects with constant rate of change, and restrict the allowed state constraints to linear inequalities. This greatly limits the expressivity of the problems that these approaches can solve. In this work we present Scotty, a planning system for hybrid activity and trajectory planning problems. Unlike other continuous time planners, Scotty can solve a broad class of expressive robotic planning problems by supporting convex quadratic constraints on state variables and control variables that are jointly constrained and that affect multiple state variables simultaneously. In order to efficiently generate practical plans for coordinated mobile robots over long horizons, our approach employs recent methods in convex optimization combined with methods for planning with relaxed planning graphs and heuristic forward search. The contributions of this thesis are threefold. First, we introduce a convex, goal-directed scheduling and trajectory planning problem. To solve this problem, we present the ScottyConvexPath planner, which reformulates the problem as a Second Order Cone Program (SOCP). Our formulation allows us to efficiently compute robot trajectories with first order dynamics over long horizons. While straightforward formulations are not convex, we present a convex model that does not require state, control or time discretization. Second, we introduce the ScottyActivity planner, a state of the art hybrid activity and trajectory planner that interleaves heuristic forward search with delete relaxations and consistency checks using our convex model. Finally, we present ScottyPath, a qualitative state plan planner that computes control and obstacle-free state trajectories for robots in order to satisfy the temporally extended goals and constraints that ScottyActivity imposes. ScottyPath finds obstacle-free paths in which all robots are guaranteed to always remain within obstacle-free safe regions, which are computed in advance. We introduce several new robotic planning domains, that we use to evaluate the scalability of our planning system and compare the performance of our approach against other prior methods. Our results show that ScottyActivity performs similarly to other state of the art heuristic forward search activity planners, while solving much more expressive robotic planning problems. On the other hand, ScottyPath can generate obstacle-free paths where robots are contained in obstacle-free convex regions more than two orders of magnitude faster than alternative mixed-integer approaches.

Book Neural Networks and Artificial Intelligence

Download or read book Neural Networks and Artificial Intelligence written by Vladimir Golovko and published by Springer. This book was released on 2014-05-27 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Neural Networks and Artificial Intelligence, ICNNAI 2014, held in Brest, Belarus, in June 2014. The 19 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in topical sections on forest resource management; artificial intelligence by neural networks; optimization; classification; fuzzy approach; machine intelligence; analytical approach; mobile robot; real world application.

Book Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments

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.

Book Motion Planning for Humanoid Robots

Download or read book Motion Planning for Humanoid Robots written by Kensuke Harada and published by Springer Science & Business Media. This book was released on 2010-08-12 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on humanoid robots has been mostly with the aim of developing robots that can replace humans in the performance of certain tasks. Motion planning for these robots can be quite difficult, due to their complex kinematics, dynamics and environment. It is consequently one of the key research topics in humanoid robotics research and the last few years have witnessed considerable progress in the field. Motion Planning for Humanoid Robots surveys the remarkable recent advancement in both the theoretical and the practical aspects of humanoid motion planning. Various motion planning frameworks are presented in Motion Planning for Humanoid Robots, including one for skill coordination and learning, and one for manipulating and grasping tasks. The problem of planning sequences of contacts that support acyclic motion in a highly constrained environment is addressed and a motion planner that enables a humanoid robot to push an object to a desired location on a cluttered table is described. The main areas of interest include: • whole body motion planning, • task planning, • biped gait planning, and • sensor feedback for motion planning. Torque-level control of multi-contact behavior, autonomous manipulation of moving obstacles, and movement control and planning architecture are also covered. Motion Planning for Humanoid Robots will help readers to understand the current research on humanoid motion planning. It is written for industrial engineers, advanced undergraduate and postgraduate students.

Book Multi Robot Motion Planning

Download or read book Multi Robot Motion Planning written by Kiril Solovey and published by . This book was released on 2017 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: