Field Validation of an Anti-Collision System with Situational Awareness for a Wave-Propelled USV

Wave-propelled unmanned surface vehicles (USVs) utilize environmental forces for propulsion, eliminating the need for conventional energy systems and enabling sustainable, long-duration missions. However, their dependence on external conditions results in low speeds, limited maneuverability, and increased susceptibility to environmental influences. Moreover, ensuring safe navigation requires continuous monitoring of both dynamic obstacles, such as other vessels, and static hazards, such as land, shallows, and submerged objects. This research presents a system designed to address the unique navigational challenges faced by wave-propelled USVs. The system integrates anti-collision and anti-grounding functionalities, employing Automatic Identification System (AIS) data and Electronic Navigational Charts (ENC) to enhance situational awareness. The anti-collision module utilizes a scenario-based model predictive control algorithm (SB-MPC) to calculate optimal maneuvers, while the anti-grounding functionality relies on digital charts stored onboard as point clouds for rapid retrieval and real-time decision-making. The architecture was developed and tested on the AutoNaut, a 5-meter-long wave-propelled USV, demonstrating its effectiveness through simulations and field experiments under various maritime scenarios.