Ocean front detection and tracking using a team of heterogeneous marine vehicles

Abstract Ocean monitoring is an expensive and time consuming endeavor, but it can be made more efficient through the use of teams autonomous robots. In this paper, we present a system for identification tracking ocean fronts by coordinating sampling efforts heterogeneous team surface vehicles (ASVs) underwater (AUVs). The primary contributions study are (1) our algorithm performing coordination using general autonomy principles: Sequential Allocation Monte Carlo Tree Search (SA‐MCTS) which incorporates domain knowledge into environmental estimation both augmenting standard Gaussian process with nearest neighbors prior planning in drifting reference frame, (2) decision support user interface to help human operators oversee system, (3) demonstration system's operation 2‐week long deployment Gulf Mexico four Slocum gliders two robotic samplers. With these contributions, aim bridge gap between state art algorithms marine vehicle methods that have been tested large‐scale field trials. This paper presents first general, heuristic‐based, multi‐robot extended mission.