Time-optimal path planning for underwater vehicles in obstacle constrained environments

This paper addresses the time-optimal path planning problem for underwater vehicles in obstacle-constrained environments. It is assumed that the vehicles can move at variable speeds but their dynamics are subject to bounded curvature and turn rate. We present a novel pose-based search algorithm, which is a modified A* algorithm to find time-optimal paths between a given pair of vehicle poses including 2-D positions and orientations. The algorithm relies on an adaptive pruning technique for exploration in a high-dimensional configuration space consisting of vehicle poses. The proposed algorithm is validated by thorough simulations for different obstacle-constrained scenarios, and the results were compared with the Dubins paths. It is shown that the algorithm is computationally efficient and produced time-optimal paths which are significantly faster than the Dubins paths.