SVF-RRT*: A Stream-Based VF-RRT* for USVs Path Planning Considering Ocean Currents
Weilong Zhang, Liang Shan, Lu Chang, Yuewei Dai
Abstract
In a large-scale oceanic environment with spatially variable ocean currents, it is vital for unmanned surface vehicles (USVs) to navigate with a safe and energy-efficient path. In this letter, a stream-based VF-RRT* (SVF-RRT*) is proposed for path planning in ocean current fields defined by the stream function. Firstly, SVF-RRT* quantifies the extent to which a feasible path goes against currents with a parameter termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">upstream coefficient</i> . Secondly, a heuristic interval is constructed based on the stream function and adjusted by the coefficient. Then, SVF-RRT* employs biased sampling and tree pruning to facilitate convergence. Sampling nodes possessing a stream value outside the interval are rejected with an adaptive probability. Meanwhile, nodes in the exploration tree outside the interval or with a cost higher than the path are discarded. Furthermore, SVF-RRT* utilizes the upstream coefficient to update the extended direction of the tree. Finally, simulation results show that SVF-RRT* accelerates the convergence of upstream cost and generates a smoother path for USVs.