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In this paper, under unforeseen circumstances, a dynamics-constrained global-local (DGL) hybrid path planning scheme incorporating global path planning and local hierarchical architecture is created for an autonomous surface vehicle (ASV) with constrained dynamics. By encapsulating ASV safety area into Theta*-like heuristics, global path planning algorithm is developed to optimally generate sparse waypoints which are sufficiently clear to constraints. To deal with dynamically unforeseen environments, a local hierarchy is established by fuzzy decision-making (FDM) and fine dynamic window (FDW) layers, which are responsible for large- and close-range collision avoidance, respectively, by governing surge and yaw velocity guidance signals. With the aid of the FDW, constrained dynamics pertaining to the ASV, i.e., actuatable surge/yaw velocities and accelerations, are elaboratively embedded into local path planning, which in turn governs trackable collision-avoidance local path. By inserting virtual waypoints onto the globally optimal path, a seamless interface between global and local path-planning mechanism is devised, and thereby contributing to the entire DGL hybrid path planning scheme. Simulations and comparisons in various real-world geographies demonstrate the effectiveness and superiority of the proposed DGL hybrid path planning scheme.
Wang et al. (Wed,) studied this question.