Abstract
The study is concerned with the problem of online planning low-cost cooperative paths; those are energy-efficient, easy-to-execute, and low collision probability for unmanned surface vehicles (USVs) based on the artificial vector field and environmental heuristics. First, we propose an artificial vector field method by following the global optimally path and the current to maximize the known environmental information. Then, to improve the optimal rapidly exploring random tree (RRT*) based planner by the environment heuristics, a Gaussian sampling scheme is adopted to seek for the likely samples that locate near obstacles. Meanwhile, a multisampling strategy is proposed to choose low-cost path tree extensions locally. The vector field guidance, the Gaussian sampling scheme, and the multisampling strategy are used to improve the efficiency of RRT* to obtain a low-cost path for the virtual leader of USVs. To promote the accuracy of collision detection during the execution process of RRT*, an ellipse function-based bounding box for USVs is proposed with the consideration of the current. Finally, an information consensus scheme is employed to quickly calculate cooperative paths for a fleet of USVs guided by the virtual leader. Simulation results show that our online cooperative path planning method is performed well in the practical marine environment.
Highlights
The online path planning (OPP) module is essential for unmanned surface vehicles (USVs) when unreliable or delayed communication links between human and USVs exist
The bounding box definition considers the velocities of USV and the current, helping to improve the accuracy of the collision detection (CD) process compared to traditional bounding boxes
This article proposes a heuristically sampling-based random method to plan for energy-efficient, easy-to-execute, and low collision probability paths for USVs in the practical marine environment
Summary
The online path planning (OPP) module is essential for unmanned surface vehicles (USVs) when unreliable or delayed communication links between human and USVs exist. The environmental current field can be used as the heuristics for designing an energy-efficient path planning method. The formation control problem for USVs was addressed by a distributed strategy based on virtual structure strategy.[21] A hierarchical control framework and relevant algorithms were proposed for autonomous navigation of USVs.[22] A three-layered architecture was devised for the real-time implementation of USV OA problem.[23] An improved APF method was responsible for avoiding obstacles smoothly.[24] An improved APF method was employed using ring-shaped repulsion for collision avoidance and OA.[25] The full-state regulation control problem for USVs under disturbances was solved by Wang et al.[26] Accurate trajectory tracking control problem of USVs disturbed by complex marine environments was addressed by Wang et al.[27,28]. (2) The vector field following Gaussian sampling and multisampling schemes is used to improve the efficiency of RRT* to obtain a low-cost path for the virtual leader of USVs. The cooperative path planning strategy is investigated based on the distributed consensus. The cooperative path planning strategy is investigated based on the distributed consensus. (3) A bounding box construction method is presented to improve the collision detection (CD) accuracy by taking the velocities of USVs and the current into account
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