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An introduction to the techniques and algorithms of the newest field in robotics. Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.
Proceedings from the annual Robotics: Science and Systems conference, presenting state-of-the-art research on the algorithmic and mathematical foundations of robotics, robotics applications, and robotics systems. Robotics: Science and Systems II spans all areas of robotics, bringing together researchers working on the algorithmic and mathematical foundations of robotics, robotics applications, and analysis of robotics systems. This volume presents the proceedings of the second annual Robotics: Science and Systems conference, held in August 2006. Papers report state-of-the-art research on topics as diverse as Legged Robotics, Reconfigurable Robots, Biomimetic Robots, Manipulation, Humanoid Robotics, Telerobotics, Haptics, Motion Planning, Collision Avoidance, Robot Vision and Perception, Bayesian Techniques, Machine Learning, Mobile Robots, and Multi-robot systems.
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