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Titlebook: SLAM Techniques Application for Mobile Robot in Rough Terrain; Andrii Kudriashov,Tomasz Buratowski,Piotr Małka Book 2020 The Editor(s) (if

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书目名称SLAM Techniques Application for Mobile Robot in Rough Terrain
编辑Andrii Kudriashov,Tomasz Buratowski,Piotr Małka
视频video
概述Confirms the robustness and efficiency of a SLAM-based integrated mobile robot approach to inspection tasks.Showcases applications of mobile robots to motion and inspection in rough and hard-to-access
丛书名称Mechanisms and Machine Science
图书封面Titlebook: SLAM Techniques Application for Mobile Robot in Rough Terrain;  Andrii Kudriashov,Tomasz Buratowski,Piotr Małka Book 2020 The Editor(s) (if
描述.This book presents the development of SLAM-based mobile robot control systems as an integrated approach that combines the localization, mapping and motion control fields, and reviews several techniques that represent the basics of the mathematical description of wheeled robots, their navigation and path planning approaches, localization and map creating techniques. It examines SLAM paradigms and Bayesian recursive state and map estimation techniques, which include Kalman and particle filtering, and enable the development of a SLAM-based integrated system for the inspection task performed. The system’s development is divided into two phases: a single-robot approach and multirobot inspection system. The book describes an original approach to 2D SLAM in multi-floor buildings that covers each 2D level map, as well as continuous 3D pose tracking, and views the multirobot inspection system as a group of homogeneous mobile robots. The last part of the book is dedicated to multirobot map creation and the development of path planning solutions, which allow the robots’ homogeneous behavior and configuration to be used to develop a multirobot system without theoretical limitations on the num
出版日期Book 2020
关键词mobile robots; SLAM; control systems; Mechatronics; robot motion; Robotics; robot adaptation; versatile pip
版次1
doihttps://doi.org/10.1007/978-3-030-48981-6
isbn_softcover978-3-030-48983-0
isbn_ebook978-3-030-48981-6Series ISSN 2211-0984 Series E-ISSN 2211-0992
issn_series 2211-0984
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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SLAM as Probabilistic Robotics Framework Approach,he robot’s pose and map are presented as parts of a probabilistic framework. The Bayesian recursive estimation definition and the Bayes filter implementations, like Kalman and discrete particle filters, were studied here. The map estimation is based on three- and two-dimensional occupancy grids. Las
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SLAM as Probabilistic Robotics Framework Approach,t part of this chapter connects these two estimation values into a common one technique that performs they simultaneously. Three different SLAM paradigms—EKF-based, particle-based and Graph-based or Topographic SLAM—have been discussed.
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