| Oceanographic research and marine environment monitoring mission nowadays are urgently demanding an autonomous platform that can autonomously cover persistent and wide-range mission in dynamic ocean environment. Currently these marine missions are generally performed by traditional platforms, such as ships buoys satellites moorings AUVs or ROVs. The platforms either depend on traditional energy or lack of autonomous mobile capability to cover longtime and wide-range mission. In this paper we are going to study the wave-propelled autonomous surface vehicle, a novel autonomous ocean monitoring platform with the capability to convert ocean wave for forward propulsion. And equipped with control and communication model, photovoltaic system and kinds of sensors, the vehicle can be applied to longtime monitoring mission.For marine operation efficiency and accuracy, path planning for wave-propelled surface vehicle in marine mission becomes a necessity. Available classical path planning algorithms are generally designed either without any consideration of ocean current or assuming it to be steady, which may lead to suboptimal or even infeasible path. Besides, optimal path planning demands the prediction of forward speed. The variability of ocean wave, however, makes the forward speed of the vehicle no longer directly controllable and unpredictable, which will result in more difficulty in path planning.Aiming in path planning for the wave-propelled vehicle, in this paper we firstly build a dynamic model of the vehicle based on Kane’s methods, which can predict the vehicle speed, and verify it with simulations and pool trails. Then a path planning method based on level set is presented, combing the predictive current with the vehicle forward speed predicted from the built dynamic model and the predictive wave state, to find the time-optimal path for the wave-propelled vehicle in dynamic ocean environment. Finally a dynamic path planning method based on level set methods is developed. |
