Abstract:
This paper proposes a general framework for distributed coverage control of mobile robotic sensors. We pose the multiagent coverage problem as an optimization problem ove...Show MoreMetadata
Abstract:
This paper proposes a general framework for distributed coverage control of mobile robotic sensors. We pose the multiagent coverage problem as an optimization problem over the space of density functions. We show that the popular locational optimization framework for coverage can be viewed as a special case of optimizing the Kullback-Leibler divergence in the space of density functions. We also see that more general approaches to distributed coverage control can be formulated based on minimizing different notions of distances. In particular we consider the L2-distance as a possible metric to design distributed coverage control laws.
Published in: 2018 IEEE Conference on Decision and Control (CDC)
Date of Conference: 17-19 December 2018
Date Added to IEEE Xplore: 20 January 2019
ISBN Information: