Autonomous Oil Spill Detection: Mission Planning for ASVs and AUVs with Static Recharging

Abstract

In this paper, a mission planning method for oil spill detection using multiple Autonomous Underwater Vehicles (AUVs) and Autonomous Surface Vehicles (ASVs) is presented. Deploying multiple marine robots provides the opportunity for efficient autonomous water sampling and leak detection. Considering the large operation area of monitoring and survey missions, the endurance of marine robots and manual recharging is a big limitation. In this work, the energy constraints are considered and a planning approach for battery recharging using charging stations is proposed. The proposed method uses a Genetic Algorithm (GA) to optimize the trajectories of ASVs and AUVs together with the locations of charging stations to minimize the mission completion time and energy cost. A realistic mission scenario is simulated to test the performance and show the capabilities. The presented mission planning algorithm is adaptable to different mission scales, environmental constraints, vehicle types and counts.