Path planning optimization for unmanned sailboat in complex marine environment

The path planning optimization problem of unmanned sailboats in the complex marine environment is investigated by considering the maneuvering characteristics of unmanned sailboats and the influence of sudden obstacles. The fusion algorithm based on improved adaptive ant colony optimization and rolling window method (RIACO) is proposed for unmanned sailboat path planning, considering that ant colony optimization (ACO) has good global search ability and rolling window method (RWM) has better local obstacle avoidance capability. In this study, an obstacle avoidance model for unmanned sailboat is introduced in an unknown environment, and RWM is integrated to monitor the environment for real-time obstacle avoidance. To achieve the globally optimal path combined with real-time obstacle avoidance, ACO is improved based on optimization objectives of path length, time duration, and safety performance. Moreover, the Bezier curve is adopted to smooth the path turning point to make it easier for unmanned sailboat navigation. Finally, the reasonableness and superiority of the proposed method are proved through multiple sets of simulation comparison experiments.