Intelligent Robotics and Autonomous AgentsRonald C. Arkin. editorRobot shaping: An Experiment in Behavior Engineering,Marco Dorigo and Marco Colombetti, 1997Behavior-Based roboticsRonald C. Arkin. 1998Layered Learning in Multiagent Systems: A Winning Approach to Robotic SoccerPeter Stone. 2000Evolutionary Robotics: The Biology, Intelligence, and Technology of self-OrganizinMachinesStefano nolfi and dario floreano. 2000Reasoning about rational agentsMichael Wooldridge, 2000Introduction to al roboticsRobin r. murphy, 2000Strategic Negotiation in Multiagent environmentsSarit Kraus. 2001Mechanics of robotic manipulationMatthew T Mason. 2001Designing Sociable robotsCynthia L Breazeal, 2002Introduction to Autonomous mobile robeRoland siegwart and Illah R Nourbakhsh, 2004Introduction to autonomous mobile robotsRoland Siegwart and Illah r Nourbakhsha Bradford BookThe Mit PressCambridge MassachusettsLondon, Englando 2004 Massachusetts Institute of TechnologyAll rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisherThis book was set in Times roman by the authors using adobe frameMaker 7.0Printed and bound in the united States of americaLibrary of Congress Cataloging-in-Publication DataSiegwart, RolandIntroduction to autonomous mobile robots / Roland Siegwart and Illah Nourbakhshp cm -(Intelligent robotics and autonomous agents)A Bradford bookIncludes bibliographical references and indexISBN 0-262-19502-X(hc: alk. paper)1. Mobile robots 2. Autonomous robots. I Nourbakhsh Illah reza. 1970-Il. Title. lll seriesTJ211415.S542004629892dc222003059349To Luzia and my children Janina, Malin and Y anik who give me their support and freedomto grow every day--RSTo my parents Susi and Y vo who opened my eyes--RSTo Marti who is my love and my inspiration--IRNTo my parents Fatemeh and Mahmoud who let me disassemble and investigate everythingin our home—IRNSlides and exercises that go with this book are available onhttp://www.mobilerobots.orgContentsAcknowledgmentsPreface1 Introduction1.1 Introduction1. 2 An Overview of the book2 Locomotion131 Introduction132. 1. 1 Key issues for locomotion162.2 Legged Mobile robots2.2.1 Leg configurations and stability2.2.2 Examples of legged robot locomotion212.3 Wheeled Mobile robots2.3. 1 Wheeled locomotion: the design space312.3.2 Wheeled locomotion: case studiesMobile robot kinematics473.1 Introduction473.2 Kinematic Models and Constraints3.2.1 Representing robot position483.2.2 Forward kinematic models513. 2. 3 Wheel kinematic constraints533.2.4 Robot kinematic constraints613.2. 5 Examples: robot kinematic models and constraints3.3 Mobile robot maneuverability673.3. 1 Degree of mobility673.3.2 Degree of steerability713.3.3 Robot maneuverabilityvIllContents3.4 Mobile robot Workspace743.4.1 Degrees of freedom743. 4.2 Holonomic robots753.4.3 Path and trajectory considerations3. 5 Beyond Basic Kinematics3.6 Motion Control(Kinematic Control813.6. 1 Open loop control(trajectory-following813.6.2 Feedback control824 Perception894.1 Sensors for mobile robots4.1.1 Sensor classification894.1.2 Characterizing sensor performance924.1.3 Wheel/motor sensors974. 1.4 Heading sensors984.1.5 Ground-based beacons1014.1.6 Active ranging1044.1.7 Motion/speed sensors1154. 1. 8 Vision-based sensors1174.2 Representing Uncertainty1454.2. 1 Statistical representation1454.2.2 Error propagation: combining uncertain measurements1494.3 Feature Extraction1514.3. 1 Feature extraction based on range data(laser, ultrasonic, vision-basedranging)1544.3.2 Visual appearance based feature extraction163Mobile robot localization1815.1 Introduction1815.2 The Challenge of Localization: Noise and Aliasing1825.2.1 Sensor noise1835.2.2 Sensor aliasing1845.2. 3 Effector noise1855.2.4 An error model for odometric position estimation1865.3 To Localize or not to Localize: Localization-Based Navigation versusProgrammed Solutions1915.4 Belief Representation1945.4.1 Single-hypothesis belief1945.4.2 Multiple-hypothesis belief196Contents5.5 Map representation2005.5.1 Continuous representations2005.5.2 Decomposition strategies2035.5. 3 State of the art: current challenges in map representation2105.6 Probabilistic Map -Based Localization2125.6.1 Introduction2125.6.2 Markov localization2145.6 3 Kalman filter localization2275.7 Other Examples of Localization Systems2445.7. 1 Landmark-based navigatio2455.7.2 Globally unique localization2465.7.3 Positioning beacon systems2485.7.4 Route-based localization2495.8 Autonomous Map building2505.8.1 The stochastic map technique2505.8.2 Other mapping techniques2536 Planning and Navigation2576.1 Introduction2576.2 Competences for Navigation: Planning and reacting2586.2.1 Path planning2596.2.2 Obstacle avoidance2726.3 Navigation Architectures2916.3. 1 Modularity for code reuse and sharing2916.3.2 Control localization2916.3.3 Techniques for decomposition2926.3.4 Case studies: tiered robot architectures298Bibliography305Books305Papers306Referenced Webpages314Interesting Internet Links to Mobile robots314Index