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Scalable control of decentralised sensor platforms

  • This paper describes an information-theoretic approach to decentralised and coordinated control of multi-robot sensor systems. It builds on techniques long established for the related problem of Decentralised Data Fusion (DDF). The DDF architecture uses information measures to communicate state estimates in a network of sensors. For coordinated control of robot sensors, the control objective becomes maximisation of these information measures. A decentralised coordinated control architecture is presented. The approach taken seeks to achieve scalable solutions that maintain consistent probabalistic sensor fusion and payoff formulations. It inherits the many benefits of the DDF method including scalability, seamless handling of sub-system activation and deactivation, and interoperability among heterogeneous units. These features are demonstrated through application to practical multi-feature localisation problems on a team of indoor robots equipped with laser range finders.

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Metadaten
Author:Ben Grocholsky, Alexei Makarenko, Tobias Kaupp, Hugh F. Durrant-Whyte
DOI:https://doi.org/10.1007/3-540-36978-3_7
ISBN:978-3-540-02111-7
ISBN:978-3-540-36978-3
Parent Title (English):Information Processing in Sensor Networks ; Lecture Notes in Computer Science (LNCS, Volume 2634)
Publisher:Springer
Place of publication:Berlin, Heidelberg
Editor:Feng Zhao, Leonidas Guibas
Document Type:Part of a Book
Language:English
Year of publication:2003
Release Date:2023/08/11
Pages/Size:17
First Page:96
Last Page:112
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