Mission Planning for Multiple Autonomous Underwater Vehicles with Constrained In Situ Recharging

Persistent operation of Autonomous Underwater Vehicles (AUVs) without manual interruption for recharging saves time and total cost for offshore monitoring and data collection applications. In order to facilitate AUVs for long mission durations without ship support, they can be equipped with docking capabilities to recharge in situ at Wave Energy Converter (WEC) with dock recharging stations. However, the power generated at the recharging stations may be constrained depending on the sea conditions. Therefore, a robust mission planning framework is proposed using a centralized Evolutionary Algorithm (EA) and a decentralized Monte Carlo Tree Search (MCTS) method. Both methods incorporate the charge availability constraint at the recharging station in addition to the maximum charge capacity of each AUV. The planner utilizes a time-varying power profile of irregular waves incident at WECs for dock charging and generates efficient mission plans for AUVs by optimizing their time to visit the dock based on the imposed constraint. The effects of increasing the number of AUVs, increasing the number of points of interest in the mission area, and varying sea state on the mission duration are also analyzed.