Infinitesimal Shape-Similarity for Characterization and Control of Bearing-Only Multirobot Formations

When organizing robots into formations, the interplay between the underlying network topology of the team and the sensing and communication modalities available to the individual robots has a fundamental effect on what types of formations are possible. The purpose of this article is to characterize...

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Veröffentlicht in:IEEE transactions on robotics Jg. 37; H. 6; S. 1921 - 1935
Hauptverfasser: Buckley, Ian, Egerstedt, Magnus
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.12.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Distributed robot systems
formation control
Formations
Multi-robot systems
Multiple robots
multirobot systems
Network topologies
Network topology
networked robots
Rigidity
Robot kinematics
Robot sensing systems
Robots
Sensors
Shape
Similarity
ISSN:1552-3098, 1941-0468
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Zusammenfassung:When organizing robots into formations, the interplay between the underlying network topology of the team and the sensing and communication modalities available to the individual robots has a fundamental effect on what types of formations are possible. The purpose of this article is to characterize the available motions of formations in which relative angles between robots equipped with bearing-only sensors are maintained. First, infinitesimal shape-similarity, a property of frameworks for which maintaining certain angles between robots ensures that the formation is invariant to translation, rotation, and uniform scaling, is examined; the shape-similarity matrix is redeveloped, and results on its nullspace are presented. Second, triangulations, a class of frameworks, are shown to be infinitesimally shape-similar. Finally, the coupling between network topology and robot capabilities is examined through the design of a decentralized heterogeneous formation-control strategy for a class of triangulations in which all robots are equipped with bearing-only sensors and a single robot can measure distances; the formation-control strategy is demonstrated on a team of differential-drive robots.
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ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2021.3072549