Globally Optimal Coverage for Non-convex Environments with Mobile Sensor Networks

The paper investigates the problem of achieving globally optimal coverage for non-convex grid environments with a network of mobile sensor nodes. A distributed algorithm is proposed to solve the problem, which is locally implementable on individual sensor. That is, each mobile sensor only requires to update its current position to an adjacent location with certain probability relying on its coverage costs at current location and adjacent locations. It shows that under the proposed algorithm, a network of mobile sensors will eventually converge to a globally optimal configuration minimizing the coverage cost with probability one. Both rigorous analysis and simulations are provided to illustrate the global convergence result.