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

Lu DONG; Ailing XIONG

doi:10.11959/j.issn.2096-6652.202229

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

Papers and Reports | 更新时间：2024-06-05

- Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart
- Chinese Journal of Intelligent Science and Technology Vol. 4, Issue 2, Pages: 264-276(2022)
- 作者机构：
  
  1. 东南大学网络空间安全学院，江苏南京 211189
  2. 东南大学自动化学院，江苏南京 210096
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-6652.202229
  CLC： TP242.6
- Published Online：2022-06，
  
  Published：15 June 2022
- 稿件说明：
移动端阅览
Lu DONG, Ailing XIONG. Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 264-276.
DOI：

Lu DONG, Ailing XIONG. Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 264-276. DOI： 10.11959/j.issn.2096-6652.202229.

摘要

针对在多移动障碍船的复杂动态环境下无人水面艇的路径规划问题，设计了一种基于改进 RRT*-Smart的无人艇路径规划方法（RTSNew）。该方法首先优化了节点采样方式，在以无人艇为原点的极坐标系中进行采样，采用椭圆形的采样点范围约束以避免无效采样，增加了历史路径缓存池以充分利用历史路径。该优化大幅降低了计算量，提高了路径规划的速度。其次，改进了节点拓展方式，为了避免将动态障碍作为静态障碍处理，给每个拓展节点增加时间信息以实现动态碰撞检测，对动态障碍运动信息的充分利用大幅提高了路径的可行性。同时，考虑到无人艇的操纵性，增加了节点拓展的角度约束以保证路径平滑。最后，对移动障碍船增加虚拟障碍，使得规划路径符合《国际海上避碰规则》（COLREGS）。基于 VREP 平台进行了无人艇航行仿真实验和对比实验，结果表明，在多障碍船的复杂动态环境下，该方法能够使无人艇高效、安全地抵达终点，相较于人工势场法和传统RRT*-Smart方法，该方法在规划效率、路径优化、安全性方面均表现优异，并且保证运动路径遵守COLREGS。提出的方法较好地解决了传统方法中将动态障碍当作静态障碍处理、未考虑COLREGS、计算量大且效率低、不适用于多移动障碍船的复杂动态环境等问题。

Abstract

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.

关键词

Keywords

references

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