Here is a comprehensive presentation of methodology for the design and synthesis of an intelligent complex robotic system, connecting formal tools from discrete system theory, artificial intelligence, neural network, and fuzzy logic. The necessary methods for solving real time action planning, coordination and control problems are described. A notable chapter presents a new approach to intelligent robotic agent control acting in a realworld environment based on a lifelong learning approach combining cognitive and reactive capabilities. Another key feature is the homogeneous description of all solutions and methods based on system theory formalism.
Intelligent Robotic Systems: Design, Planning, and Control
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Editorial Reviews
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`The book is clearly written and well organized. It covers recent approaches to the field, including those originated during author's own research. It can be used by experts who look for recent advances in intelligent robotic systems. Also, the book can be recommended as a textbook for an advanced course in the area'
Journal of General Systems, 31:1 (2002)
Journal of General Systems, 31:1 (2002)
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Inside This Book
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First Sentence:
In a complex system using robotic agents, knowledge about the surrounding environment determines the structure and methodologies used to control and coordinate the system, which leads to an increase in the intelligence of the individual system components. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
workstation serviced, sensor data combination, main input file, inverse kinematics module, primary fuzzy sets, sinusoidal units, geometric track, trajectory planner, robotic workcell, trajectory planning problem, robotic cell, kinematic matrix, computed torque controller, gripping points, effector end, path planner, coupled neural network, motion planner, machining task, nominal dynamics, grip points, robot kinematics, excluded surfaces, robotic agent, cell controller Key Phrases - Capitalized Phrases (CAPs): (learn more)
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In a complex system using robotic agents, knowledge about the surrounding environment determines the structure and methodologies used to control and coordinate the system, which leads to an increase in the intelligence of the individual system components. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
workstation serviced, sensor data combination, main input file, inverse kinematics module, primary fuzzy sets, sinusoidal units, geometric track, trajectory planner, robotic workcell, trajectory planning problem, robotic cell, kinematic matrix, computed torque controller, gripping points, effector end, path planner, coupled neural network, motion planner, machining task, nominal dynamics, grip points, robot kinematics, excluded surfaces, robotic agent, cell controller Key Phrases - Capitalized Phrases (CAPs): (learn more)
The Groplan New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 21
books:
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1
book
cites this book:
- Intelligent Robots and Systems by V. Graefe in Back Matter (1), and Back Matter (2)
- Systems Design by Isim University in Front Matter (1), and Front Matter (2)
- Computer Integrated Design and Manufacturing by David D. Bedworth in Back Matter
- Neural Network Systems Techniques and Applications, Seven-Volume Set: Control and Dynamic Systems, Neural Network Systems Techniques and Applications, Volume 7 by Cornelius T. Leondes in Back Matter
- Artificl Intell Instructrs Manual Tx by Author Unknown in Back Matter
See all 21 books this book cites
- Flexible Robot Dynamics and Controls (IFSR International Series on Systems Science and Engineering) by Rush D. Robinett III in Front Matter
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