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Area-constrained coverage optimization by robotic sensor networks
J. Cortés
Proceedings of the IEEE Conference on Decision and Control, Cancun, Mexico, 2008, pp. 1018-1023

Abstract

This paper studies robotic sensor networks performing coverage optimization with area constraints. The network coverage of the environment is a function of the robot locations and the partition of the space. The area of the region assigned to each robot is constrained to be a pre-specified amount. We characterize the optimal network configurations as center generalized Voronoi configurations. The generalized Voronoi partition depends on a set of weights, one per robot, assigned to the network. We design a Jacobi iterative algorithm to find the weight assignment whose corresponding generalized Voronoi partition satisfies the area constraints. This algorithm is distributed over the generalized Delaunay graph. We also design the ``move-to-center-and-compute-weight'' motion coordination algorithm that steers the robotic network towards the set of center generalized Voronoi configurations while monotonically optimizing the coverage of the environment. Various simulations illustrate our results.

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Mechanical and Aerospace Engineering, University of California, San Diego
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