收稿日期: 2019-03-20
网络出版日期: 2019-10-25
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
Received date: 2019-03-20
Online published: 2019-10-25
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.
瞿栋, 彭艳, 蒲华燕, 罗均, 黄承义, 柯俊 . 面向障碍速度不确定性的无人艇动态避碰[J]. 上海大学学报(自然科学版), 2019 , 25(5) : 655 -667 . DOI: 10.12066/j.issn.1007-2861.2164
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.
| [1] | Ska?ckauskas P, Sokolovskij E . Analysis of the hybrid global path planning algorithm for different environments[J]. Transport and Telecommunication Journal, 2019,20(1):1-11. |
| [2] | Wei X, Wen D S, Song Z X , et al. A star identification algorithm based on radial and dynamic cyclic features of star pattern[J]. Advances in Space Research, 2019,63(7):2245-2259. |
| [3] | Campbell S, Naeem W, Irwin G W . A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres[J]. Annual Reviews in Control, 2012,36(2):267-283. |
| [4] | Huang Y M, Chen L Y, Van Gelder P H A J M . Generalized velocity obstacle algorithm for preventing ship collisions at sea[J]. Ocean Engineering, 2019,173:142-156. |
| [5] | 梁山, 刘娟, 鲜晓东 . 一种考虑机器人尺寸约束的动态窗避障方法[J]. 控制工程, 2011,18(6):872-876. |
| [6] | Kuwata Y, Wolf M T, Zarzhitsky D , et al. Safe maritime navigation with COLREGS using velocity obstacles[C]// International Conference on Intelligent Robots and Systems (IROS). 2011: 4728-4734. |
| [7] | Fulgenzi C, Spalanzani A, Laugier C . Dynamic obstacle avoidance in uncertain environment combining PVOs and occupancy grid[C]// International Conference on Robotics and Automation. 2007: 1610-1616. |
| [8] | 张洋洋, 瞿栋, 柯俊 , 等. 基于速度障碍法和动态窗口法的无人水面艇动态避障[J]. 上海大学学报(自然科学版), 2017,23(1):1-16. |
| [9] | 杨秀霞, 张毅, 周硙 . 一种动态不确定环境下 UAV 自主避障算法[J]. 系统工程与电子技术, 2010,39(11):2546-2552. |
| [10] | 杨秀霞, 周硙, 张毅 . 三维动态不确定 UAV 自主避障算法[J]. 电光与控制, 2017,24(9):1-5. |
| [11] | 张成钢, 孙茂相 . 移动机器人在障碍物具有不确定性时的运动规划[J]. 机器人, 2003,25(3):278-281. |
| [12] | 卢艳爽 . 水面无人艇路径规划算法研究[D]. 哈尔滨: 哈尔滨工程大学, 2010. |
| [13] | Johansen T A, Perez T, Cristofaro A . Ship collision avoidance and COLREGS compliance using simulation-based control behavior selection with predictive hazard assessment[J]. IEEE Transactions on Intelligent Transportation Systems, 2016,17(12):3407-3422. |
| [14] | Park J, Choi J, Choi H T . COLREGS-compliant path planning considering time-varying trajectory uncertainty of autonomous surface vehicle[J]. Electronics Letters, 2019,55(4):222-224. |
| [15] | Larson J, Bruch M, Ebken J . Autonomous navigation and obstacle avoidance for unmanned surface vehicles[C]// Unmanned Systems Technology Ⅷ. 2006: 623007. |
| [16] | Fiorini P, Shiller Z . Motion planning in dynamic environments using velocity obstacles[J]. International Journal of Robotics Research, 1998,17(7):760-772. |
| [17] | Pietrzykowski Z, Uriasz J . The ship domain: a criterion of navigational safety assessment in an open sea area[J]. Journal of Navigation, 2009,62(1):93-108. |
| [18] | Woerner K . Multi-contact protocol-constrained collision avoidance for autonomous marine vehicles[D]. Cambridge: Massachusetts Institute of Technology, 2016. |
| [19] | Naeem W, Irwin G W, Yang A . COLREGs-based collision avoidance strategies for unmanned surface vehicles[J]. Mechatronics, 2012,22(6):669-678. |
| [20] | Benjamin M R, Curcio J A . COLREGS-based navigation of autonomous marine vehicles[C]// 2004 IEEE/OES Autonomous Underwater Vehicles. 2004: 32-39. |
| [21] | Campbell S, Abu-Tair M, Naeem W . An automatic COLREGs-compliant obstacle avoidance system for an unmanned surface vehicle[J]. Journal of Engineering for the Maritime Environment, 2014,228(2):108-121. |
| [22] | Stenersen T . Guidance system for autonomous surface vehicle[D]. Trondheim: Norwegian University of Science and Technology, 2015. |
| [23] | 李小毛, 张鑫, 王文涛 , 等. 基于3D 激光雷达的无人水面艇海上目标检测[J]. 上海大学学报(自然科学版), 2017,23(1):27-36. |
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