On Trajectory Homotopy for USV Swarm Penetration with Interception Risk

This paper aims to address a trajectory homotopy optimization framework for clusters of unmanned surface vehicles (USVs) to solve the problem of dynamic penetration mission planning with interception risk. An improved penetration trajectory homotopy algorithm is used to predict the location of intercepting USV. To improve the efficiency of the solution for penetration path planning, a novel variable-time mechanism has been developed to adapt to the updated delay time. An incremental occupancy grid map, which includes static obstacles and dynamic enemy USV combinations, is constructed using a Gaussian probability field algorithm. A collaborative cluster penetration strategy is proposed to enhance the success rate of penetration under asymmetric conditions. Furthermore, a luring Dubins trajectory planning approach is proposed to interfere with enemy interception. An advanced penetration homotopy algorithm is used for the remaining USVs to quickly achieve penetration. The simulation results indicated that the collaborative swarm penetration strategy and IPTH algorithm can solve the USV swarm penetration mission planning problem with interception risk.