Chinese Journal of Intelligent Science and Technology ›› 2022, Vol. 4 ›› Issue (2): 264-276.doi: 10.11959/j.issn.2096-6652.202229

• Papers and Reports • Previous Articles     Next Articles

Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart

Lu DONG1, Ailing XIONG2   

  1. 1 School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China
    2 School of Automation, Southeast University, Nanjing 210096, China
  • Online:2022-06-15 Published:2022-06-01
  • Supported by:
    The National Natural Science Foundation of China(62173251);Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control;Fundamental Research Funds for the Central Universities


Aiming at the path planning problem of unmanned surface vehicle (USV) in complex dynamic environment with moving multi-obstacle ships, a path planning method based on improved RRT*-Smart (RTSNew) was designed.Firstly, the sampling mode of nodes was optimized, nodes were sampled in the polar coordinate system with USV as the origin, an elliptical sampling range constraint was adopted to avoid invalid sampling, and a historical path buffer pool was used to make full use of the historical path.The optimization greatly reduced the amount of calculation and improved the speed of path planning.Secondly, the expansion mode of nodes was improved.In order to avoid treating dynamic obstacles as static obstacles, time information was added to each node to realize dynamic collision detection and the full use of dynamic obstacles motion information greatly improves the feasibility of the planned path.At the same time, considering the maneuverability of USV, the angle constraint was added in expansion of nodes to ensure smooth path.Finally, virtual obstacles were designed to mobile obstacle ships to make the planned path comply with International Regulations for Preventing Collisions at Sea (COLREGS).Based on VREP platform, the USV navigation simulation experiments and comparative experiments were carried out.The results show that RTSNew can make USV reach the destination efficiently and safely, and it performs better in planning efficiency, path optimization and path security than traditional methods in complex dynamic environment with multi-obstacle ships.RTSNew ensures that the motion path complies with COLREGS, and solves the problems of traditional methods: treating the dynamic obstacles as static obstacles, ignoring COLREGS, large amount of calculation and low efficiency, not suitable for the complex dynamic environment with moving multi-obstacle ships.

Key words: unmanned surface vehicle, RRT*-Smart, path planning, dynamic collision detection, COLREGS

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