TY  - BOOK
AU  - Siegwart,Roland
AU  - Nourbakhsh,Illah Reza
AU  - Scaramuzza,Davide
TI  - Introduction to autonomous mobile robots
T2  - Intelligent robotics and autonomous agents
SN  - 9780262015356 (hbk.)
AV  - TJ211.415 .S54 2011
U1  - 629.892 22
PY  - 2011///
CY  - Cambridge, Mass.
PB  - MIT Press
KW  - Mobile robots
KW  - Autonomous robots
N1  - Includes bibliographical references and index; Machine generated contents note; 1; Introduction --; 1.1; Introduction --; 1.2; An Overview of the Book --; 2; Locomotion --; 2.1; Introduction --; 2.1.1; Key issues for locomotion --; 2.2; Legged Mobile Robots --; 2.2.1; Leg configurations and stability --; 2.2.2; Consideration of dynamics --; 2.2.3; Examples of legged robot locomotion --; 2.3; Wheeled Mobile Robots --; 2.3.1; Wheeled locomotion: The design space --; 2.3.2; Wheeled locomotion: Case studies --; 2.4; Aerial Mobile Robots --; 2.4.1; Introduction --; 2.4.2; Aircraft configurations --; 2.4.3; State of the art in autonomous VTOL --; 2.5; Problems --; 3; Mobile Robot Kinematics --; 3.1; Introduction --; 3.2; Kinematic Models and Constraints --; 3.2.1; Representing robot position --; 3.2.2; Forward kinematic models --; 3.2.3; Wheel kinematic constraints --; 3.2.4; Robot kinematic constraints --; 3.2.5; Examples: Robot kinematic models and constraints; 3.3; Mobile Robot Maneuverability --; 3.3.1; Degree of mobility --; g; 4.2.5; Structure from stereo --; 4.2.6; Structure from motion --; 4.2.7; Motion and optical flow --; 4.2.8; Color tracking --; 4.3; Fundamentals of Image Processing --; 4.3.1; Image filtering --; 4.3.2; Edge detection --; 4.3.3; Computing image similarity --; 4.4; Feature Extraction --; 4.5; Image Feature Extraction: Interest Point Detectors --; 4.5.1; Introduction --; 4.5.2; Properties of the ideal feature detector --; 4.5.3; Corner detectors --; 4.5.4; Invariance to photometric and geometric changes --; 4.5.5; Blob detectors --; 4.6; Place Recognition --; 4.6.1; Introduction --; 4.6.2; From bag of features to visual words --; 4.6.3; Efficient location recognition by using an inverted file --; 4.6.4; Geometric verification for robust place recognition --; 4.6.5; Applications --; 4.6.6; Other image representations for place recognition --; 4.7; Feature Extraction Based on Range Data (Laser, Ultrasonic) --; 4.7.1; Line fitting --; 4.7.2; Six line-extraction algorithms; 4.7.3; Range histogram features --; 4.7.4; Extracting other geometric features --; 4.8; Problems --; 5; Mobile Robot Localization --; 5.1; Introduction --; 5.2; The Challenge of Localization: Noise and Aliasing --; 5.2.1; Sensor noise --; 5.2.2; Sensor aliasing --; 5.2.3; Effector noise --; 5.2.4; An error model for odometric position estimation --; 5.3; To Localize or Not to Localize: Localization-Based Navigation Versus Programmed Solutions --; 5.4; Belief Representation --; 5.4.1; Single-hypothesis belief --; 5.4.2; Multiple-hypothesis belief --; 5.5; Map Representation --; 5.5.1; Continuous representations --; 5.5.2; Decomposition strategies --; 5.5.3; State of the art: Current challenges in map representation --; 5.6; Probabilistic Map-Based Localization --; 5.6.1; Introduction --; 5.6.2; The robot localization problem --; 5.6.3; Basic concepts of probability theory --; 5.6.4; Terminology --; 5.6.5; The ingredients of probabilistic map-based localization; 5.6.6; Classification of localization problems --; 5.6.7; Markov localization --; 5.6.8; Kalman filter localization --; 5.7; Other Examples of Localization Systems --; 5.7.1; Landmark-based navigation --; 5.7.2; Globally unique localization --; 5.7.3; Positioning beacon systems --; 5.7.4; Route-based localization --; 5.8; Autonomous Map Building --; 5.8.1; Introduction --; 5.8.2; SLAM: The simultaneous localization and mapping problem --; 5.8.3; Mathematical definition of SLAM --; 5.8.4; Extended Kalman Filter (EKF) SLAM --; 5.8.5; Visual SLAM with a single camera --; 5.8.6; Discussion on EKF SLAM --; 5.8.7; Graph-based SLAM --; 5.8.8; Particle filter SLAM --; 5.8.9; Open challenges in SLAM --; 5.8.10; Open source SLAM software and other resources --; 5.9; Problems --; 6; Planning and Navigation --; 6.1; Introduction --; 6.2; Competences for Navigation: Planning and Reacting --; 6.3; Path Planning --; 6.3.1; Graph search --; 6.3.2; Potential field path planning; 6.4; Obstacle avoidance --; 6.4.1; Bug algorithm --; 6.4.2; Vector field histogram --; 6.4.3; The bubble band technique --; Curvature velocity techniques --; 6.4.5; Dynamic window approaches --; 6.4.6; The Schlegel approach to obstacle avoidance --; 6.4.7; Nearness diagram --; 6.4.8; Gradient method --; 6.4.9; Adding dynamic constraints --; 6.4.10; Other approaches --; 6.4.11; Overview --; 6.5; Navigation Architectures --; 6.5.1; Modularity for code reuse and sharing --; 6.5.2; Control localization --; 6.5.3; Techniques for decomposition --; 6.5.4; Case studies: tiered robot architectures --; 6.6; Problems --; Bibliography --; Books --; Papers --; Referenced Webpages
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