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Details about  Sensing, Intelligence, Motion by Vladimir J. Lumelsky, very rare robotics book.

Sensing, Intelligence, Motion by Vladimir J. Lumelsky, very rare robotics book. See original listing
Sensing-Intelligence-Motion-by-Vladimir-J-Lumelsky-very-rare-robotics-book
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Item condition:
Very Good
Ended:
17 Mar, 2012 16:09:36 GMT
Starting bid:
£28.00
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Item location:
London, London, United Kingdom
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eBay item number:
160761405339
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Item specifics
Condition:
Very Good: A book that has been read and does not look new, but is in excellent condition. No obvious damage to ... Read moreabout the condition
Author:

Vladimir Lumelsky
Publication Year:

22/11/2005

 Subject:

Philosophy & Psychology
Format:

Hardback

 Subject 2:

Psychology: Professional & General
Language:

English

 ISBN:

9780471707400
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Detailed item information

Description
Describing techniques for handling motion planning tasks in unstructured environments, Sensing, Intelligence Motion fills the need for one comprehensive reference on the subject.

Key Features
Author(s)Vladimir Lumelsky
PublisherJohn Wiley and Sons Ltd
Date of Publication22/11/2005
Language(s)English
FormatHardback
ISBN-100471707406
ISBN-139780471707400
GenrePsychology: Professional & General

Publication Data
Place of PublicationNew York
Country of PublicationUnited States
ImprintJohn Wiley & Sons Inc
Content NoteIllustrations

Dimensions
Weight717 g
Width161 mm
Height238 mm
Spine25 mm
Pagination456

Description
Table Of ContentsPreface. Acknowledgments. 1 Motion Planning-Introduction. 1.1 Introduction. 1.2 Basic Concepts. 1.2.1 Robot? What Robot? 1.2.2 Space. Objects. 1.2.3 Input Information. Sensing. 1.2.4 Degrees of Freedom. Coordinate Systems. 1.2.5 Motion Control. 1.2.6 Robot Programming. 1.2.7 Motion Planning. 2 A Quick Sketch of Major Issues in Robotics. 2.1 Kinematics. 2.2 Statics. 2.3 Dynamics. 2.4 Feedback Control. 2.5 Compliant Motion. 2.6 Trajectory Modification. 2.7 Collision Avoidance. 2.8 Motion Planning with Complete Information. 2.9 Motion Planning with Incomplete Information. 2.9.1 The Beginnings. 2.9.2 Maze-to-Graph Transition. 2.9.3 Sensor-Based Motion Planning. 2.10 Exercises. 3 Motion Planning for a Mobile Robot. 3.1 The Model. 3.2 Universal Lower Bound for the Path Planning Problem. 3.3 Basic Algorithms. 3.3.1 First Basic Algorithm: Bug1. 3.3.2 Second Basic Algorithm: Bug2. 3.4 Combining Good Features of Basic Algorithms. 3.5 Going After Tighter Bounds. 3.6 Vision and Motion Planning. 3.6.1 The Model. 3.6.2 Algorithm VisBug-21. 3.6.3 Algorithm VisBug-22. 3.7 From a Point Robot to a Physical Robot. 3.8 Other Approaches. 3.9 Which Algorithm to Choose? 3.10 Discussion. 3.11 Exercises. 4 Accounting for Body Dynamics: The Jogger's Problem. 4.1 Problem Statement. 4.2 Maximum Turn Strategy. 4.2.1 The Model. 4.2.2 Sketching the Approach. 4.2.3 Velocity Constraints. Minimum Time Braking. 4.2.4 Optimal Straight-Line Motion. 4.2.5 Dynamics and Collision Avoidance. 4.2.6 The Algorithm. 4.2.7 Examples. 4.3 Minimum Time Strategy. 4.3.1 The Model. 4.3.2 Sketching the Approach. 4.3.3 Dynamics and Collision Avoidance. 4.3.4 Canonical Solution. 4.3.5 Near-Canonical Solution. 4.3.6 The Algorithm. 4.3.7 Convergence. Computational Complexity. 4.3.8 Examples. 5 Motion Planning for Two-Dimensional Arm Manipulators. 5.1 Introduction. 5.1.1 Model and Definitions. 5.2 Planar Revolute-Revolute (RR) Arm. 5.2.1 Analysis. 5.2.2 Algorithm. 5.2.3 Step Planning. 5.2.4 Example. 5.2.5 Motion Planning with Vision and Proximity Sensing. 5.2.6 Concluding Remarks. 5.3 Distinct Kinematic Configurations of RR Arm. 5.4 Prismatic-Prismatic (PP, or Cartesian) Arm. 5.5 Revolute-Prismatic (RP) Arm with Parallel Links. 5.6 Revolute-Prismatic (RP) Arm with Perpendicular Links. 5.7 Prismatic-Revolute (PR) Arm. 5.8 Topology of Arm's Free Configuration Space. 5.8.1 Workspace; Configuration Space. 5.8.2 Interaction Between the Robot and Obstacles. 5.8.3 Uniform Local Connectedness. 5.8.4 The General Case of 2-DOF Arm Manipulators. 5.9 Appendix. 5.10 Exercises. 6 Motion Planning for Three-Dimensional Arm Manipulators. 6.1 Introduction. 6.2 The Case of the PPP (Cartesian) Arm. 6.2.1 Model, Definitions, and Terminology. 6.2.2 The Approach. 6.2.3 Topology of W-Obstacles and C-Obstacles. 6.2.4 Connectivity of C. 6.2.5 Algorithm. 6.2.6 Examples. 6.3 Three-Link XXP Arm Manipulators. 6.3.1 Robot Arm Representation Spaces. 6.3.2 Monotonicity of Joint Space. 6.3.3 Connectivity of Jf. 6.3.4 Retraction of Jf. 6.3.5 Configuration Space and Its Retract. 6.3.6 Connectivity Graph. 6.3.7 Lifting 2D Algorithms into 3D. 6.3.8 Step Planning. 6.3.9 Discussion. 6.4 Other XXX Arms. 7 Human Performance in Motion Planning. 7.1 Introduction. 7.2 Preliminary Observations. 7.2.1 Moving in a Maze. 7.2.2 Moving an Arm Manipulator. 7.2.3 Conclusions and Plan for Experiment Design. 7.3 Experiment Design. 7.3.1 The Setup. 7.3.2 Test Protocol. 7.4 Results-Experiment One. 7.4.1 Principal Components Analysis. 7.4.2 Nonparametric
Author BiographyVLADIMIR J. LUMELSKY, PhD, is Consolidated Papers Professor of Engineering, University of Wisconsin-Madison. Prior to his current appointment, he held positions with Ford Motor Research Laboratories, General Electric Research Center, and Yale University. Dr. Lumelsky is the author or coauthor of more than 200 scholarly publications.

Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Sensing, Intelligence, Motion by Vladimir J. Lumelsky.

An informative look at how humans and robots move in an unstructured world.

Hardback in excellent condition, only read once or twice.

Very rare book, not available to buy for anything less than £80, grab yourself a bargain!

Thanks for looking.

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