Mission-Driven Trajectory Homotopy to Explore Dynamic Coverage of USV-UAV Systems

This article aims to address the challenge of dynamically exploring coverage for unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs) system with mission-driven framework in an obstacle environment. A novel cross-domain collaborative exploration and coverage (CDCEC) framework is proposed to enhance the overall performance of the proposed full and optimal coverage paths. The multimodal full-coverage path planning (FCPP) mapping algorithm is designed to generate a comprehensive evaluation trajectory in environments with varying distributions of obstacles. The mission allocation method is established for multi-USV FCPP based on the distributions of obstacles. A mission-driven trajectory homotopy is presented to dynamically explore coverage in a game confrontation environment. A set of game strategies for USV-UAV cross-domain collaboration is proposed and selected in term of decision trees rely on the game scenario. The results of the simulations and experiments demonstrate that the CDCEC framework can achieve compatibility with both full and optimal CPP trajectories and solve the incremental exploration of the dynamic coverage problem.