Cooperative coverage using receding horizon control

We present a path planning algorithm for cooperative surveillance using a set of heterogeneous unmanned vehicles. The paper describes our overall framework and algorithm for the computation of trajectories that maximize spatio-temporal coverage while satisfying hard constraints such as collision avoidance and specifications on initial and final positions. An Integer Programming (IP)-based strategy for successfully operating within these constraints is developed. IP is applied over a receding planning horizon with terminal cost to reduce the computational effort of the planner and to incorporate feedback. Simulation and results are presented to demonstrate the efficacy of the proposed approach.

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