## Computational Principles of Mobile RoboticsMobile robotics is a multidisciplinary field involving both computer science and engineering. Addressing the design of automated systems, it lies at the intersection of artificial intelligence, computational vision, and robotics. This textbook for advanced undergraduates and graduate students emphasizes algorithms for a range of strategies for locomotion, sensing, and reasoning. It concentrates on wheeled and legged mobile robots but discusses a variety of other propulsion systems. The new edition includes advances in robotics and intelligent machines over the last ten years, including significant coverage of SLAM (simultaneous localization and mapping) and multi-robot systems. It includes additional mathematical background and an extensive list of sample problems. Various mathematical techniques that were assumed in the first edition are now briefly introduced in appendices at the end of the text to make the book more self-contained. Researchers as well as students in the field of mobile robotics will appreciate this comprehensive treatment of state-of-the-art methods and key technologies. |

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### Cuprins

1 Overview and motivation | 1 |

2 Fundamental problems | 18 |

part I Locomotion and Perception | 29 |

part II Representation and Planning | 165 |

Probability and statistics | 335 |

Linear systems matrices and filtering | 341 |

Markov models | 346 |

353 | |

381 | |

### Alte ediții - Afișați-le pe toate

Computational Principles of Mobile Robotics Gregory Dudek,Michael Jenkin Previzualizare limitată - 2010 |

Computational Principles of Mobile Robotics Gregory Dudek,Michael Richard MacLean Jenkin,Michael Jenkin Previzualizare limitată - 2000 |

Computational Principles of Mobile Robotics Gregory Dudek,Michael Jenkin Nu există previzualizare disponibilă - 2010 |

### Termeni și expresii frecvente

algorithm approach architecture Artiﬁcial autonomous robots behavior camera collective complex computational conﬁguration consider constraints constructed coordinate covariance matrix deﬁned described developed devices differential drive difﬁcult direction distance distribution edge efﬁcient environment error example ﬁnal ﬁnd ﬁrst ﬂoor function geometric given global goal graph Hough transform identiﬁed input inverse kinematics Kalman ﬁlter kinematics known landmarks laser linear localization Markov Markov localization matrix measurements mechanisms mobile robots motion navigation nodes noise object obstacles operator optimal orientation output path planning pixel plane planner point robot polygon pose position estimate potential ﬁeld problem quadtree reﬂected region represent representation robot moves robot’s position robotic systems rotation sample sensing sensor signal simple solution sonar space speciﬁc stereopsis strategies structure subsumption architecture sufﬁcient surface target task techniques typically vector vehicle velocity vertex visibility graph vision visual Voronoi diagram wheels