Scalable control of decentralised sensor platforms

Authors:
Ben Grocholsky;Alexei Makarenko;Tobias Kaupp;Hugh F. Durrant-Whyte
Affiliations:
Australian Centre for Field Robotics, University of Sydney, Australia;Australian Centre for Field Robotics, University of Sydney, Australia;Australian Centre for Field Robotics, University of Sydney, Australia;Australian Centre for Field Robotics, University of Sydney, Australia
Venue:
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Year:
2003

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Abstract

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.