A Backstepping Approach for Networked Control of a Multi-Vehicle Team of Autonomous Under-Ice Profilers
Ian Buckley, Michael West, Magnus Egerstedt, Catherine Colello Walker · 2019
Recent advances in the capabilities of autonomous underwater vehicles suggest their growing utility in support of oceanographic inquiry. Towards developing autonomous systems to aid in monitoring and exploration of the polar, under-ice environment, this paper examines multi-vehicle teams consisting of autonomous profilers, a class of low-cost autonomous underwater vehicles that can only actuate their depth. Existing research on the under-ice environment documents the existence of depth-dependent ocean currents, which can be opportunistically leveraged to coordinate the motion of a team of autonomous profilers. As such, this paper proposes a backstepping control strategy that enables teams of autonomous profilers to execute established networked control algorithms; the backstepping controllers are examined through simulation and deployment on a team of differential-drive robots.