无人艇集群在海上公共区域航行需要考虑互相避障以及水面其他障碍的规避问题,故提出一种无人艇集群避障算法解决该问题。算法改进了速度障碍法,考虑障碍物位置和速度以估计未来时间窗口下可能发生碰撞的锥形区域,并规划出可行域半平面。之后引入海事避碰规则进一步约束无人艇的避碰方向和可行域范围。多障碍场景下,通过在若干个可行域的交集上寻找最优的避碰速度矢量,可引导无人艇避障。算法中各无人艇相互独立,不存在中心节点。进行了仿真验证,将数十条无人艇划分为多个集群进行相互避障测试。仿真结果表明,该方法能够有效地避免无人艇集群之间的碰撞,具有较好的鲁棒性和实时性。
In this paper, an Unmanned Surface Vehicle (USV) cluster avoidance algorithm is proposed to address the problem of mutual avoidance and obstacle avoidance in the public area of the sea. The algorithm improves the speed obstacle method by taking into account the position and speed of obstacles to estimate the cone region where a collision may occur in the future time window, and plans out the feasible domain half-plane. Moreover, the International Regulations for Preventing Collisions at Sea (COLREGs) are introduced to constrain the avoidance direction and feasible domain range of USVs. In the case of multiple obstacles, by finding the optimal avoidance speed vector on the intersection of several feasible domains, it can guide USVs to avoid obstacles. This algorithm is independent for each USV, without a central node. The effectiveness of the proposed algorithm is verified by simulation, which divides dozens of USVs into multiple clusters for mutual avoidance tests. The simulation results demonstrate that this method can effectively prevent collisions between USV clusters, and has good robustness and real-time performance.
2024,46(9): 66-70 收稿日期:2023-05-10
DOI:10.3404/j.issn.1672-7649.2024.09.011
分类号:U664.82
基金项目:海洋防务创新基金资助项目(JJ-2021-702-01);装发预研项目(450121215k2943MX)
作者简介:周则兴(1995 – ),男,硕士,工程师,研究方向为无人艇控制技术
参考文献:
[1] CAMPBELL S, NAEEM W, IRWIN GW. A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres[J]. Annual Reviews in Control, 2012, 36(2): 267-83.
[2] SUN Z, SUN H, LI P, et al. Self-organizing cooperative pursuit strategy for multi-usv with dynamic obstacle ships[J]. Journal of Marine Science and Engineering, 2022, 10(5): 562.
[3] 申云磊, 高霄鹏. 无人艇的研究现状与进展[J]. 船电技术, 2018, 38(9): 7-10.
[4] 姜俊, 彭刚, 郭世宏. 对联合登陆战役中反水雷作战的思考[J]. 水雷战与舰船防护, 2009, 17(3): 60-62.
[5] 白灵, 赵珈玉, 鞠岩松. 人工智能在船舶航行数学建模中的应用[J]. 舰船科学技术, 2023, 45(8): 173-176.
BAI L, ZHAO J Y, JU Y S. Application of artificial intelligence in mathematical modeling of ship navigation[J]. Ship Science and Technology, 2023, 45(8): 173-176.
[6] WOLF MT, BURDICK JW. Artificial potential functions for highway driving with collision avoidance[C]// Proceedings of the 2008 IEEE International Conference on Robotics and Automation, 2008.
[7] CHEN Y B, LUO G-c, MEI Y S, et al. UAV path planning using artificial potential field method updated by optimal control theory[J]. International Journal of Systems Science, 2016, 47(6): 1407-1420.
[8] HUANG Y, CHEN L, CHEN P, et al. Ship collision avoidance methods: State-of-the-art [J]. Safety Science, 2020, 121: 451-473.
[9] TAN G, ZHUANG J, ZOU J, et al. Artificial potential field-based swarm finding of the unmanned surface vehicles in the dynamic ocean environment [J]. International Journal of Advanced Robotic Systems, 2020, 17(3): 1-16.
[10] VAN DEN BERG J, SNAPE J, GUY SJ, et al. Reciprocal collision avoidance with acceleration-velocity obstacles[C]// Proceedings of the 2011 IEEE International Conference on Robotics and Automation, 2011: 3475-3482.
[11] BERG JVD, GUY SJ, LIN M, et al. Reciprocal n-body collision avoidance [M]. Robotics research. Springer, 2011.
[12] SNAPE J, VAN DEN BERG J, GUY SJ, et al. The hybrid reciprocal velocity obstacle[J]. IEEE Transactions on Robotics, 2011, 27(4): 696-706.
[13] BAREISS D, VAN DEN BERG J. Generalized reciprocal collision avoidance[J]. The International Journal of Robotics Research, 2015, 34(12): 1501-1514.
[14] 吕红光, 裴天琪, 尹勇, 等. 智能船舶背景下《1972年国际海上避碰规则》的修正[J]. 上海海事大学学报, 2020, 41(4): 117-124.
[15] 金建海, 周则兴, 张波, 等. 无人艇航行仿真关键技术研究[J]. 系统仿真学报, 2021, 33(12): 2846-2853.