Electronics and Electrical Engineering and Control

Local path planning algorithm for UAV based on improved velocity obstacle method

  • Hua GUO ,
  • Xiaohe GUO
Expand
  • School of Aircraft Engineering,Nanchang Hangkong University,Nanchang 330000,China
E-mail: 34009@nchu.edu.cn

Received date: 2022-06-08

  Revised date: 2022-07-28

  Accepted date: 2022-09-29

  Online published: 2022-10-14

Abstract

To solve the real-time and safety problems in UAV local path replanning based on environment awareness, a local path avoidance planning algorithm is proposed based on the improved velocity obstacle method. The traditional velocity obstacle method is extended to the three-dimensional space, and a three-dimensional spatial velocity obstacle model is established to transform the motion uncertainty of maneuvering dynamic obstacles in the velocity space into position uncertainty, with better real-time performance and improved obstacle avoidance level and safety margin. By defining and introducing adaptive threat distance, the utilization rate of the original trajectory of the UAV in the obstacle avoidance process is improved. The optimal speed of spatial autonomous obstacle avoidance is solved using spatial geometric analysis, and dynamic real-time planning of local paths is achieved. The timeliness, feasibility and effectiveness of the algorithm are verified by comparing the simulation results of local path obstacle avoidance planning under three scenarios: encounter, pursuit and crossover.

Cite this article

Hua GUO , Xiaohe GUO . Local path planning algorithm for UAV based on improved velocity obstacle method[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(11) : 327586 -327586 . DOI: 10.7527/S1000-6893.2022.27586

References

1 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 Science201647(6): 1407-1420.
2 彭闪, 殷苑, 田峰, 等. 无人机航迹规划算法综述[J]. 数字技术与应用202240(4): 77-79.
  PENG S, YIN Y, TIAN F, et al. Overview of UAV path planning algorithms[J]. Digital Technology & Application202240(4): 77-79 (in Chinese).
3 徐文钰, 敖海跃, 刘燕斌. 基于鸽群优化算法的多无人机局部航迹重规划[J]. 战术导弹技术2022(1): 46-52.
  XU W Y, AO H Y, LIU Y B. Local path re-planning of multi-UAVs based on pigeon-inspired optimization[J]. Tactical Missile Technology2022(1): 46-52 (in Chinese).
4 张宏宏, 甘旭升, 毛亿, 等. 无人机避障算法综述[J]. 航空兵器202128(5): 53-63.
  ZHANG H H, GAN X S, MAO Y, et al. Review of UAV obstacle avoidance algorithms[J]. Aero Weaponry202128(5): 53-63 (in Chinese).
5 刘祥, 叶晓明, 王泉斌, 等. 无人水面艇局部路径规划算法研究综述[J]. 中国舰船研究202116(S1): 1-10.
  LIU X, YE X M, WANG Q B, et al. Review on the research of local path planning algorithms for unmanned surface vehicles[J]. Chinese Journal of Ship Research202116(S1): 1-10 (in Chinese).
6 JIN Z, YAN B, YE R. The flight navigation planning based on potential field ant colony algorithm[C]∥Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018). Paris: Atlantis Press, 2018: 200-204.
7 李二超, 王玉华. 改进人工势场法的移动机器人避障轨迹研究[J]. 计算机工程与应用202258(6): 296-304.
  LI E C, WANG Y H. Research on obstacle avoidance trajectory of mobile robot based on improved artificial potential field[J]. Computer Engineering and Applications202258(6): 296-304 (in Chinese).
8 张建英, 刘暾. 基于人工势场法的移动机器人最优路径规划[J]. 航空学报200728(S1): 183-188.
  ZHANG J Y, LIU T. Optimized path planning of mobile robot based on artificial potential field[J]. Acta Aeronautica et Astronautica Sinica200728(S1): 183-188 (in Chinese).
9 魏瑞轩, 周凯. 面向位置环境的无人机障碍规避制导率设计[J]. 系统工程与电子技术201525(9): 2096-2101.
  WEI R X, ZHOU K. Design of UAV Obstacle avoidance guidance rate oriented to location environment[J]. Systems Engineering and Electronic Technology201525(9): 2096-2101 (in Chinese).
10 宋宇, 王志明. 面向无人机三维航迹规划的改进粒子群优化算法[J]. 传感器与微系统201938(3): 144-146.
  SONG Y, WANG Z M. Improved PSO algorithm for UAV 3D track planning[J]. Transducer and Microsystem Technologies201938(3): 144-146 (in Chinese).
11 黄书召, 田军委, 乔路, 等. 基于改进遗传算法的无人机路径规划[J]. 计算机应用202141(2): 390-397.
  HUANG S Z, TIAN J W, QIAO L, et al. Unmanned aerial vehicle path planning based on improved genetic algorithm[J]. Journal of Computer Applications202141(2): 390-397 (in Chinese).
12 徐鹏. 基于模拟退火算法的机器人路径规划与研究[J]. 科技广场2011(1): 42-44.
  XU P. Planning and research of robot path based on simulated annealing path[J]. Science Mosaic2011(1): 42-44 (in Chinese).
13 FIORINI P, SHILLER Z. Motion planning in dynamic environments using the relative velocity paradigm[C]∥ Proceedings IEEE International Conference on Robotics and Automation. Piscataway: IEEE Press, 2002: 560-565.
14 黄永龙, 仲训昱. 基于改进速度障碍法的多机器人避碰规划算法[J]. 计算机工程与应用201248(32): 47-51, 207.
  HUANG Y L, ZHONG X Y. Improved velocity obstacles-based collision avoidance algorithm for multiple mobile robots[J]. Computer Engineering and Applications201248(32): 47-51, 207 (in Chinese).
15 DURAND N, BARNIER N. Does ATM need centralized coordination? Autonomous conflict resolution analysis in a constrained speed environment[J]. Air Traffic Control Quarterly201523(4): 325-346.
16 HAN S C, BANG H, YOO C S. Proportional navigation-based collision avoidance for UAVs[J].International Journal of Control, Automation and Systems20097(4): 553-565.
17 王泽坤, 吴明功, 温祥西. 基于速度障碍法的飞行冲突解脱与恢复策略[J]. 北京航空航天大学201945(7): 1294-1302.
  WANG Z K, WU M G, WEN X X. Flight conflict relief and recovery strategy based on speed obstacle method [J]. Journal of Beijing University of Aeronautics and Astronautics201945(7): 1294-1302 (in Chinese).
18 张宏宏, 甘旭升, 李昂, 等. 基于速度障碍法的无人机避障与航迹恢复策略[J]. 系统工程与电子技术202042(8): 1759-1767.
  ZHANG H H, GAN X S, LI A, et al. UAV obstacle avoidance and track recovery strategy based on velocity obstacle method[J]. Systems Engineering and Electronics202042(8): 1759-1767 (in Chinese).
19 杨秀霞, 华伟, 孟启源. 基于有限时间速度障碍法的UAV避障研究[J]. 弹箭与制导学报201838(5): 19-22, 26.
  YANG X X, HUA W, MENG Q Y. Study on UAV obstacle avoidance based on finite time velocity obstruction method[J]. Journal of Projectiles, Rockets, Missiles and Guidance201838(5): 19-22, 26 (in Chinese).
20 许文瑶, 贺继林. 基于改进速度障碍法的水下机器人动态避障[J]. 电光与控制202128(12): 86-90.
  XU W Y, HE J L. Dynamic obstacle avoidance for ROV based on improved velocity obstacle method[J]. Electronics Optics & Control202128(12): 86-90 (in Chinese).
21 杨秀霞, 周硙硙, 张毅. 三维动态不确定UAV自主避障算法[J]. 电光与控制201724(9): 1-5.
  YANG X X, ZHOU W W, ZHANG Y. A 3-D dynamic autonomous obstacle avoidance algorithm for UAVs[J]. Electronics Optics & Control201724(9): 1-5 (in Chinese).
22 SNAPE J, VAN DEN BERG J, GUY S J, et al. The hybrid reciprocal velocity obstacle[J]. IEEE Transactions on Robotics201127(4): 696-706.
23 CHAKRAVARTHY A, GHOSE D. Generalization of the collision cone approach for motion safety in 3-D environments[J]. Autonomous Robots201232(3): 243-266.
24 杨健. 无人机集群系统空域冲突消解方法研究[D]. 长沙: 国防科学技术大学, 2016: 11-16.
  YANG J. Study on the airspace conflict resolution problem of unmanned aerial vehicle swarm systems[D]. Changsha: National University of Defense Technology, 2016: 11-16 (in Chinese).
Outlines

/