This volume offers a novel framework for solving the path planning problems 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 work provides an effective and practical approach to solving path planning problems. The book gives details of implementations that allow a better understanding of the complexity 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.
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Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
Inside This Book
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First Sentence:
Multiple robotic systems are becoming more common with more than one robot working in the same environment, such as today's automated factories, where there is an ever increasing demand for flexible automation. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
cell decomposition approach, approximate cell decomposition, collision avoidance algorithm, motion planning problem, path planning problem, configuration space representation, configuration space approach, inverse kinematics problem, plane segment, manipulator moves, planar manipulator, polyhedron polyhedron, joint variables, path planner, robot manipulators, link parameters, goto step, joint velocity, task planner, slave process, cartesian space, instruction stream, robotics research Key Phrases - Capitalized Phrases (CAPs): (learn more)
Link Link Link, Approach Algorithm, Instruction Control New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
Multiple robotic systems are becoming more common with more than one robot working in the same environment, such as today's automated factories, where there is an ever increasing demand for flexible automation. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
cell decomposition approach, approximate cell decomposition, collision avoidance algorithm, motion planning problem, path planning problem, configuration space representation, configuration space approach, inverse kinematics problem, plane segment, manipulator moves, planar manipulator, polyhedron polyhedron, joint variables, path planner, robot manipulators, link parameters, goto step, joint velocity, task planner, slave process, cartesian space, instruction stream, robotics research Key Phrases - Capitalized Phrases (CAPs): (learn more)
Link Link Link, Approach Algorithm, Instruction Control New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
Citations (learn more)
This book cites 44
books:
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8
books
cite this book:
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- Parallel and Distributed Computing Handbook by Albert Y. Zomaya in Back Matter (1), Back Matter (2), and Back Matter (3)
- Parallel Computation Systems for Robotics: Algorithms and Architectures (Series in Robotics and Automated Systems, Vol 2) by A. Fijany in Front Matter, and Back Matter
- Robot Motion Planning (The Springer International Series in Engineering and Computer Science) by Jean-Claude Latombe in Back Matter (1), and Back Matter (2)
- Genetic Algorithms (Ieee Computer Society Press Technology Series) by Bill P. Buckles in Back Matter (1), and Back Matter (2)
- Free Space by Edward E. Kramer in Back Matter
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- Fuzzy Decision Making in Modeling and Control (World Scientific Series in Robotics and Intelligent Systems) by Joao M. C. Sousa in Front Matter
- Odour Detection by Mobile Robots by R. Andrew Russell in Front Matter
- Evolutionary Robotics: From Algorithms to Implementations (World Scientific Series in Robotics and Intelligent Systems) by Lingfeng Wang in Front Matter
- Interdisciplinary Approaches to Robot Learning by John Demiris in Front Matter
- Active Sensors for Local Planning in Mobile Robotics by Penelope Probert Smith in Front Matter
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