Decentralized Control for Optimizing Communication with Infeasible Regions
Author(s)Gil, Stephanie; Prentice IV, Samuel James; Roy, Nicholas; Rus, Daniela L
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In this paper we present a decentralized gradient-based controller that optimizes communication between mobile aerial vehicles and stationary ground sensor vehicles in an environment with infeasible regions. The formulation of our problem as a MIQP is easily implementable, and we show that the addition of a scaling matrix can improve the range of attainable converged solutions by influencing trajectories to move around infeasible regions. We demonstrate the robustness of the controller in 3D simulation with agent failure, and in 10 trials of a multi-agent hardware experiment with quadrotors and ground sensors in an indoor environment. Lastly, we provide analytical guarantees that our controller strictly minimizes a nonconvex cost along agent trajectories, a desirable property for general multi-agent coordination tasks.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Gil, Stephanie, Samuel Prentice, Nicholas Roy, and Daniela Rus. “Decentralized Control for Optimizing Communication with Infeasible Regions.” edited by Christensen, H. and O. Khatib, Robotics Research (August 2016): 363–381 © 2017 Springer International Publishing Switzerland
Author's final manuscript