Parallel and Distributed Map Merging and Localization Algorithms, Tools and Strategies for Robotic Networks / [electronic resource] :
by Rosario Aragues, Carlos Sag�u�es, Youcef Mezouar.
- VIII, 116 p. 34 illus. online resource.
- SpringerBriefs in Computer Science, 2191-5768 .
- SpringerBriefs in Computer Science, .
This 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. This work will be of interest to postgraduate students and researchers in the robotics and control communities, and will appeal to anyone with a general interest in multi-robot systems. The reader will not require any prior background knowledge, other than a basic understanding of mathematics at a graduate-student level. The coverage is largely self-contained, supported by numerous explanations and demonstrations, although references for further study are also supplied.
9783319258867
10.1007/978-3-319-25886-7 doi
Computer science. Computer communication systems. Artificial intelligence. Image processing. Robotics. Automation. Computer Science. Artificial Intelligence (incl. Robotics). Robotics and Automation. Computer Communication Networks. Image Processing and Computer Vision.