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OverviewThis work examines the challenges of distributed map merging and localization in multi-robot systems, which enables robots to acquire the knowledge of their surroundings needed to carry out coordinated tasks. After identifying the main issues associated with this problem, each chapter introduces a different distributed strategy for solving them. In addition to presenting a review of distributed algorithms for perception in localization and map merging, the text also provides the reader with the necessary tools for proposing new solutions to problems of multi-robot perception, as well as other interesting topics related to multi-robot scenarios. The coverage is largely self-contained, supported by numerous explanations and demonstrations, although references for further study are also supplied. The reader will not require any prior background knowledge, other than a basic understanding of mathematics at a graduate-student level. Full Product DetailsAuthor: Rosario Aragues , Carlos Sagüés , Youcef MezouarPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 1st ed. 2015 Dimensions: Width: 15.50cm , Height: 0.70cm , Length: 23.50cm Weight: 0.454kg ISBN: 9783319258843ISBN 10: 3319258842 Pages: 116 Publication Date: 10 November 2015 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction.- Distributed Data Association.- Distributed Localization.- Map Merging.- Real Experiments.- Conclusions.- Appendix A: Averaging Algorithms and Metropolis Weights.- Appendix B: Auxiliary Results for Distributed Localization.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |