In this video, we present a contract-based, decentralized planning approach for guarding a valuable asset by a team of autonomous unmanned surface vehicles (USV) against hostile boats in an environment with civilian traffic. The particular objective for the team of USVs is to maximize the expected time it takes a hostile boat to reach the asset. The team has to cooperatively deal with uncertainty about which boats poses an actual threat, employ active blocking to slow down the movement of boats towards the asset, and intelligently distribute themselves around the asset to optimize their future guarding opportunities. The developed planner incorporates a contract-based algorithm for allocating tasks to individual USVs through forward simulating the mission and assigning estimated utilities to candidate task allocation plans. The task allocation is based on marginal cost based contracting that allows decentralized, cooperative task negotiation among neighboring agents. The planner is capable of computing task allocation plans in real-time and is general enough to be used for a variety of scenarios. The underlying behaviors that correspond to individual tasks are optimized for two specific mission scenarios.
E. Raboin, P. ?vec, D. Nau, and S. K. Gupta. Model-Predictive Target Defense by Team of Unmanned Surface Vehicles Operating in Uncertain Environments. IEEE International Conference on Robotics and Automation (ICRA '13), Karlsruhe, Germany, May 6-10, 2013.