Abstract

Ice navigation is currently one of the important issues in path planning studies. Most studies are using sea ice models or ice charts for large-scale path planning, but the weather and ice conditions in the polar waters usually change quickly and are not easy to predict. Under these conditions, small-scale path planning that can be adjusted in time for sea ice collision avoidance is needed. This study uses marine radar imaging to reconstruct the ice navigation scene, and establishes a visual-ization function of sea ice warning on the radar image. We combine the bidirectional rapidly-exploring random tree (B-RRT) algorithm and the greedy algorithm to propose a path planning algorithm that generates various path planning schemes for ice navigation. After a number of path planning schemes are quickly generated, the path risk index proposed in this study can be used to evaluate and choose a relatively optimal path planning scheme with lower risk, as well as serve as an assistant reference for path planning decisions in ice navigation.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call