上海大学学报(自然科学版) ›› 2019, Vol. 25 ›› Issue (5): 655-667.doi: 10.12066/j.issn.1007-2861.2164

所属专题: 无人艇

• 无人艇 • 上一篇    下一篇

面向障碍速度不确定性的无人艇动态避碰

瞿栋1(), 彭艳1, 蒲华燕1, 罗均1, 黄承义2, 柯俊1   

  1. 1. 上海大学 机电工程与自动化学院, 上海 200444
    2. 国家海洋局 北海海洋工程勘察研究院, 山东 青岛 266061
  • 收稿日期:2019-03-20 出版日期:2019-10-30 发布日期:2019-10-25
  • 通讯作者: 瞿栋 E-mail:dongqu@shu.edu.cn
  • 基金资助:
    国家重点研发计划资助项目(2017YFC0806700);国家自然科学基金资助项目(61673254);上海市科研计划资助项目(17DZ1205001)

Dynamic collision avoidance for unmanned surface vessels under the uncertainty of obstacle velocity

Dong QU1(), Yan PENG1, Huayan PU1, Jun LUO1, Chengyi HUANG2, Jun KE1   

  1. 1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
    2. North Sea Engineering Survey and Research Institute, State Oceanic Administration, Qingdao 266061, Shandong, China)
  • Received:2019-03-20 Online:2019-10-30 Published:2019-10-25
  • Contact: Dong QU E-mail:dongqu@shu.edu.cn

摘要:

避碰稳定性直接关乎无人艇航行安全. 传感器对障碍速度观测的不确定性会 导致避碰策略出现跳动, 严重降低避碰稳定性. 提出不确定性条件下的速度障碍(uncertain velocity obstacle, UVO)算法, 在碰撞风险评估中采用自适应阈值的最近会遇点(closest point of approach, CPA)法, 基于国际海事避碰规则(International Regulations for Preventing Collisions at Sea, COLREGS)建立边界缓冲区, 从宏观上提升避碰过程的稳定性. 为了减少无人艇避碰角度的变化次数, 在无人艇的速度空间中对不确定性条件下的速度障碍(velocity obstacle, VO)区进行建模, 并采用梯度下降法在代价空间进行局部寻优, 从微观上提升避碰策略的稳定性. 在仿真平台下进行 UVO 算法和 VO 算法的对比实验, 结果表明 UVO 算法的避碰策略跳动次数、避碰成功率和最近会遇距离 3 项指标均优于 VO 算法. 在实艇海试中进行了对遇、交叉、追越等典型会遇场景的避碰实验, 无人艇均能安全避过运动目标. 实验结果证明了 UVO 算法具有较好稳定性和安全性.

关键词: 无人艇, 动态避碰, 速度不确定性, 速度障碍, 碰撞风险评估

Abstract:

The stability of collision avoidance is directly relate to the safety of unmanned surface vehicle (USV). However, the uncertainty of perception about the velocity of moving obstacles seriously undermine the stability of collision avoidance. Thus, an uncertain velocity obstacle (UVO) method is proposed to solve this problem. In order to improve the stability of collision avoidance at the macro level, an adaptive threshold-based closest point of approach (CPA) is adopted to assess collision risk while a boundary buffer is used to calculate the type of International Regulations for Preventing Collisions at Sea (COLREGS). To prevent changes in collision avoidance strategy, the UVO is modeled in velocity space of the USV, and a gradient descent method is used to determine local optimization of the cost function. Contrast experiments in simulation platform between UVO and VO indicate that the UVO has better performance on three indicators: strategy changes, success rate, and safe distance. Typical encounters such as head-on, crossing, and overtaking are conducted in sea trials. The USV successfully avoids each moving obstacle in the experiment. The results demonstrate the stability and safety of the UVO method.

Key words: unmanned surface vehicle (USV), dynamic collision avoidance, uncertainty of obstacle velocity, velocity obstacle, collision risk assessment

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