Study On Autonomous Sailboat Route Planning

With the development of renewable energy and artificial intelligence,their combination in industry application is also of interest.Autonomous sailboat shows the remarkable values in ocean observation and resource exploration.In this paper,the long-term route planning for autonomous sailboat is carefully studied.Many complex factors and constraints are hard to be quantificated in route planning algorithms.Hence diversified results acquired by long-term route planning methods should be kept as optional routes.The multi-dimensional dynamic programming method was employed for the long-term route planning of an autonomous sailboat from Shanghai to Qingdao.The sailed voyage length was adopted to be the third-dimension state variable.The short-term route planning between the neighboring waypoints was defined as control variable.A group of optimal routes with the minimum voyage time could be obtained corresponding to different voyage length.As the planning results shows,with the increase of state variable dimension,more optional routes were kept for the better decision support.Compared with the multi-objective evolutionary method of route planning,the multi-dimensional dynamic programming method can approach the pareto solution with shorter operation time.