Introduction to Autonomous Mobile Robots
Mobile robots range from the teleoperated Sojourner on the Mars Pathfinder mission to cleaning robots in the Paris Metro. Introduction to Autonomous Mobile Robots offers students and other interested readers an overview of the technology of mobility—the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks—including locomotion, sensing, localization, and motion planning. It discusses all facets of mobile robotics, including hardware design, wheel design, kinematics analysis, sensors and perception, localization, mapping, and robot control architectures.
The design of any successful robot involves the integration of many different disciplines, among them kinematics, signal analysis, information theory, artificial intelligence, and probability theory. Reflecting this, the book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter covers a different aspect of mobility, as the book moves from low-level to high-level details. The first two chapters explore low-level locomotory ability, examining robots' wheels and legs and the principles of kinematics. This is followed by an in-depth view of perception, including descriptions of many "off-the-shelf" sensors and an analysis of the interpretation of sensed data. The final two chapters consider the higher-level challenges of localization and cognition, discussing successful localization strategies, autonomous mapping, and navigation competence. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook for coursework or a working tool for beginners in the field.
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algorithm angle approach architecture axis behavior belief bubble band camera castor wheels cell decomposition chip color compute defined degrees of freedom depicted Dervish described detection differential-drive direction distance edge edge detection encoder environment environmental equation error example feature extraction fixed standard wheel function Gaussian geometric global goal position histogram holonomic input Kalman filter kinematic constraints laser rangefinder legs locomotion maneuverability map representation Markov localization matrix mobile robot modules motor multiple-hypothesis navigation node objects obstacle avoidance occupancy grid omnidirectional optical flow output parameters path planning perceptual pixel potential field prediction problem range sensor reference frame represents result robot chassis robot kinematics robot localization robot motion rotation sensor values shown in figure sliding constraints sonar specific speed steerable steering stereo stereo vision Swedish wheel techniques tion topological trajectory ultrasonic uncertainty update vector velocity visibility graph vision vision-based Voronoi diagram workspace
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