Download or read book Parallel Algorithms for Real time Motion Planning written by Matthew McNaughton and published by . This book was released on 2011 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "For decades, humans have dreamed of making cars that could drive themselves, so that travel would be less taxing, and the roads safer for everyone. Toward this goal, we have made strides in motion planning algorithms for autonomous cars, using a powerful new computing tool, the parallel graphics processing unit (GPU). We propose a novel five-dimensional search space formulation that includes both spatial and temporal dimensions, and respects the kinematic and dynamic constraints on a typical automobile. With this formulation, the search space grows linearly with the length of the path, compared to the exponential growth of other methods. We also propose a parallel search algorithm, using the GPU to tackle the curse of dimensionality directly and increase the number of plans that can be evaluated by an order of magnitude compared to a CPU implementation. With this larger capacity, we can evaluate a dense sampling of plans combining lateral swerves and accelerations that represent a range of effective responses to more on-road driving scenarios than have previously been addressed in the literature. We contribute a cost function that evaluates many aspects of each candidate plan, ranking them all, and allowing the behavior of the vehicle to be fine-tuned by changing the ranking. We show that the cost function can be changed on-line by a behavioral planning layer to express preferred vehicle behavior without the brittleness induced by top-down planning architectures. Our method is particularly effective at generating robust merging behaviors, which have traditionally required a delicate and failure-prone coordination between multiple planning layers. Finally, we demonstrate our proposed planner in a variety of on-road driving scenarios in both simulation and on an autonomous SUV, and make a detailed comparison with prior work."

Download or read book Obstacle Avoidance in Multi robot Systems written by Mark A. C. Gill and published by World Scientific. This book was released on 1998 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Obstacle Avoidance in Multi-robot Systems: Experiments in Parallel Genetic Algorithms offers a novel framework for solving the path planning problem for robot manipulators. Simple and efficient solutions are proposed for the path planning problem based on genetic algorithms. One of the attractive features of genetic algorithms is their ability to solve formidable problems in a robust and straightforward manner. Moreover, genetic algorithms are inherently parallel in nature, which makes them ideal candidates for parallel computing implementations.By combining the robustness of genetic algorithms with the power of parallel computers, this book provides an effective and practical approach to solving path planning problems. The book gives details of implementations that allow a better understanding of the complexities involved in the development of parallel path planning algorithms. The material presented is interdisciplinary in nature ? it combines topics from robotics, genetic algorithms, and parallel processing. The book can be used by practitioners and researchers in computer science and engineering.

Download or read book Massive Parallelism and Sampling Strategies for Robust and Real time Robotic Motion Planning written by Brian Ichter and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Motion planning is a fundamental problem in robotics, whereby one seeks to compute a low-cost trajectory from an initial state to a goal region that avoids any obstacles. Sampling-based motion planning algorithms have emerged as an effective paradigm for planning with complex, high-dimensional robotic systems. These algorithms maintain only an implicit representation of the state space, constructed by sampling the free state space and locally connecting samples (under the supervision of a collision checking module). This thesis presents approaches towards enabling real-time and robust sampling-based motion planning with improved sampling strategies and massive parallelism. In the first part of this thesis, we discuss algorithms to leverage massively parallel hardware (GPUs) to accelerate planning and to consider robustness during the planning process. We present an algorithm capable of planning at rates amenable to application within control loops, ∼10 ms. This algorithm uses approximate dynamic programming to explore the state space in a massively-parallel, near-optimal manner. We further present two algorithms capable of real-time, uncertainty-aware and perception-aware motion planning that exhaustively explore the state space via a multiobjective search. This search identifies a Pareto set of promising paths (in terms of cost and robustness) and certifies their robustness via Monte Carlo methods. We demonstrate the effectiveness of these algorithm in numerical simulations and a physical experiment on a quadrotor. In the second part of this thesis, we examine sampling-strategies for probing the state space; traditionally this has been uniform, independent, and identically distributed (i.i.d.) random points. We present a methodology for biasing the sample distribution towards regions of the state space in which the solution trajectory is likely to lie. This distribution is learned via a conditional variational autoencoder, allowing a general methodology, which can be used in combination with any sampling- based planner and can effectively exploit the underlying structure of a planning problem while maintaining the theoretical guarantees of sampling-based approaches. We also analyze the use of deterministic, low-dispersion samples instead of i.i.d. random points. We show that this allows deterministic asymptotic optimality (as opposed to probabilistic), a convergence rate bound in terms of the sample dispersion, reduced computational complexity, and improved practical performance. The technical approaches in this work are applicable to general robotic systems and lay the foundations of robustness and algorithmic speed required for robotic systems operating in the world.

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 Robotic Computing on FPGAs written by Shaoshan Liu and published by Morgan & Claypool Publishers. This book was released on 2021-06-30 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the state-of-the-art field-programmable gate array (FPGA)-based robotic computing accelerator designs and summarizes their adopted optimized techniques. This book consists of ten chapters, delving into the details of how FPGAs have been utilized in robotic perception, localization, planning, and multi-robot collaboration tasks. In addition to individual robotic tasks, this book provides detailed descriptions of how FPGAs have been used in robotic products, including commercial autonomous vehicles and space exploration robots.

Download or read book Applications of Parallel Computing in Robotics Problems written by Siavash Farzan and published by . This book was released on 2013 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many typical robotics problems involve search in high-dimensional spaces, where real-time execution is hard to be achieved. This thesis presents two case studies of parallel computation in such robotics problems. More specifically, two problems of motion planning-the Inverse Kinematics of robotic manipulators and Path Planning for mobile robots-are investigated and the contributions of parallel algorithms are highlighted. For the Inverse Kinematics problem, a novel and fast solution is proposed for general serial manipulators. This new approach relies on the computation of multiple (parallel) numerical estimations of the inverse Jacobian while it selects the current best path to the desire con- figuration of the end-effector. Unlike other iterative methods, our method converges very quickly, achieving sub-millimeter accuracy in 20.48ms in average. We demonstrate such high accuracy and the real-time performance of our method by testing it with six different robots, at both non-singular and singular configurations, including a 7-DoF redundant robot. The algorithm is implemented in C/C++ using a configurable number of POSIX threads, and it can be easily expanded to use many-core GPUs. For the Path Planning problem, a solution to the problem of smooth path planning for mobile robots in dynamic and unknown environments is presented. A novel concept of Time-Warped Grids is introduced to predict the pose of obstacles on a grid-based map and avoid collisions. The algorithm is implemented using C/C++ and the CUDA programming environment, and combines stochastic estimation (Kalman filter), Harmonic Potential Fields and a Rubber Band model, and it translates naturally into the parallel paradigm of GPU programing. The proposed method was tested using several simulation scenarios for the Pioneer P3- DX robot, which demonstrated the robustness of the algorithm by finding the optimum path in terms of smoothness, distance, and collision-free either in static or dynamic environments, even with a very large number of obstacles.

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 Parallel Computation Systems for Robotics written by A. Fijany and published by World Scientific. This book was released on 1992 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an extensive survey of the state-of-the-art research in parallel computational algorithms and architectures for robot manipulator control and simulation. It deals not only with specifics but also includes general and broader issues which serve as a useful foundation to the topic. The educational flavor of the book makes it a necessary resource for researchers, engineers and students wanting to be familiarized with the potential offered by the application of parallel processing to robotic problems, and its current issues and trends.

Download or read book Parallel Algorithms for Optimization of Dynamic Systems in Real time written by and published by . This book was released on 2014 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parallel Search Algorithms for Robot Motion Planning written by Daniel Joseph Challou and published by . This book was released on 1993 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Algorithmic Foundations of Robotics IX written by David Hsu and published by Springer. This book was released on 2010-11-18 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robotics is at the cusp of dramatic transformation. Increasingly complex robots with unprecedented autonomy are finding new applications, from medical surgery, to construction, to home services. Against this background, the algorithmic foundations of robotics are becoming more crucial than ever, in order to build robots that are fast, safe, reliable, and adaptive. Algorithms enable robots to perceive, plan, control, and learn. The design and analysis of robot algorithms raise new fundamental questions that span computer science, electrical engineering, mechanical engineering, and mathematics. These algorithms are also finding applications beyond robotics, for example, in modeling molecular motion and creating digital characters for video games and architectural simulation. The Workshop on Algorithmic Foundations of Robotics (WAFR) is a highly selective meeting of leading researchers in the field of robot algorithms. Since its creation in 1994, it has published some of the field’s most important and lasting contributions. This book contains the proceedings of the 9th WAFR, held on December 13-15, 2010 at the National University of Singapore. The 24 papers included in this book span a wide variety of topics from new theoretical insights to novel applications.

Download or read book Parallel Algorithms for Irregular Problems State of the Art written by Alfonso Ferreira and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient parallel solutions have been found to many problems. Some of them can be obtained automatically from sequential programs, using compilers. However, there is a large class of problems - irregular problems - that lack efficient solutions. IRREGULAR 94 - a workshop and summer school organized in Geneva - addressed the problems associated with the derivation of efficient solutions to irregular problems. This book, which is based on the workshop, draws on the contributions of outstanding scientists to present the state of the art in irregular problems, covering aspects ranging from scientific computing, discrete optimization, and automatic extraction of parallelism. Audience: This first book on parallel algorithms for irregular problems is of interest to advanced graduate students and researchers in parallel computer science.

Download or read book Parallel Algorithms in Computational Science written by Dieter W. Heermann and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our aim in this book is to present and enlarge upon those aspects of parallel computing that are needed by practitioners of computational science. Today al most all classical sciences, such as mathematics, physics, chemistry and biology, employ numerical methods to help gain insight into nature. In addition to the traditional numerical methods, such as matrix inversions and the like, a whole new field of computational techniques has come to assume central importance, namely the numerical simulation methods. These methods are much less fully developed than those which are usually taught in a standard numerical math ematics course. However, they form a whole new set of tools for research in the physical sciences and are applicable to a very wide range of problems. At the same time there have been not only enormous strides forward in the speed and capability of computers but also dramatic new developments in computer architecture, and particularly in parallel computers. These improvements offer exciting prospects for computer studies of physical systems, and it is the new techniques and methods connected with such computer simulations that we seek to present in this book, particularly in the light of the possibilities opened up by parallel computers. It is clearly not possible at this early stage to write a definitive book on simulation methods and parallel computing.

Download or read book 2014 International Conference on Artificial Intelligence and Software Engineering AISE2014 written by S. K. Chen, Altair Engineering Inc., California, USA and published by DEStech Publications, Inc. This book was released on 2014-02-06 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2014 International Conference on Artificial Intelligence and Software Engineering(AISE2014) aims to provide a forum for accessing to the most up-to-date and authoritative knowledge from both Artificial Intelligence and Software Engineering. AISE2014 features unique mixed topics of AI Algorithms, Data Mining, Knowledge-based Systems, Software Process and so on. The goal of this conference is to bring researchers, engineers, and students to the areas of Artificial Intelligence and Software Engineering to share experiences and original research contributions on those topics. Researchers and practitioners are invited to submit their contributions to AISE2014.

Download or read book Real time Motion Planning and Safe Navigation in Dynamic Multi robot Environments written by James Robert Bruce and published by . This book was released on 2006 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: All mobile robots share the need to navigate, creating the problem of motion planning. In multi-robot domains with agents acting in parallel, highly complex and unpredictable dynamics can arise. This leads to the need for navigation calculations to be carried out within tight time constraints, so that they can be applied before the dynamics of the environment make the calculated answer obsolete. At the same time, we want the robots to navigate robustly and operate safely without collisions. While motion planning has been used for high level robot navigation, or limited to semi-static or single-robot domains, it has often been dismissed for the real-time low-level control of agents due to the limited computational time and the unpredictable dynamics. Many robots now rely on local reactive methods for immediate control of the robot, but if the reason for avoiding motion planning is execution speed, the answer is to find planners that can meet this requirement. Recent advances in traditional path planning algorithms may offer hope in resolving this type of scalability, if they can be adapted to deal with the specific problems and constraints mobile robots face. Also, in order to maintain safety, new scalable methods for maintaining collision avoidance among multiple robots are needed in order to free motion planners from the "curse of dimensionality" when considering the safety of multiple robots with realistic physical dynamics constraints. This thesis contributes the pairing of real-time motion planning which builds on existing modern path planners, and a novel cooperative dynamics safety algorithm for high speed navigation of multiple agents in dynamic domains. It also explores near real-time kinematically limited motion planning for more complex environments. The thesis algorithms have been fully implemented and tested with success on multiple real robot platforms.

Download or read book Parallel Processing for Artificial Intelligence 2 written by V. Kumar and published by Elsevier. This book was released on 2014-06-28 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy. This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their subject: architectures (3 papers), languages (4 papers), general algorithms (6 papers), and applications (5 papers). The internationally sourced papers range from purely theoretical work, simulation studies, algorithm and architecture proposals, to implemented systems and their experimental evaluation. Since the book is a second volume in the parallel processing for AI series, it provides a continued documentation of the research and advances made in the field. The editors hope that it will inspire readers to investigate the possiblities for enhancing AI systems by parallel processing and to make new discoveries of their own!

Download or read book Parallel Computation of Robot Motion Planning Algorithms written by Julio Solano Gonzalez and published by . This book was released on 1992 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: