| 183 | 0 | 236 |
| 下载次数 | 被引频次 | 阅读次数 |
针对无人设备在执行如定点巡逻任务和货物搬运作业时，需要解决多点遍历和避障路径规划的问题，开展了一种基于改进Maklink图的全局路径规划算法研究，优化避障作业路径。首先，建立改进Maklink图作为空间模型，简化作业空间；随后，设计一种改进蚁群算法在上述空间模型内规划路径，算法采用针对多点遍历的启发式函数、禁忌搜索、局部最优处理机制和精英个体保留与额外进化策略；最后，对比实验证明了所提算法在不同任务环境下的有效性，具有更强的寻优能力和更好的稳定性，在10个案例中，相对基于概率路线图的算法和传统蚁群算法，路径长度优化提升最大分别可达21.13%和49.31%，稳定性提升最大分别可达99.56%和99.82%。
Abstract：When unmanned equipment performs tasks such as fixed-point patrol and cargo handling, it is necessary to solve the problem of multi-point traversal with obstacle avoidance path planning. This paper studies a global path planning algorithm based on improved Maklink graph to optimize the obstacle avoidance path with strong stability.Firstly,improved Maklink graph is established as the space model to simplify the work space. Then, an improved ant colony algorithm is designed to plan the path in the above space model. The algorithm adopts the heuristic function for multi-point traversal, tabu search, local optimal processing mechanism and elite individual retention and additional evolution strategy. Finally, comparative experiments show that the proposed algorithm is effective,has better optimization ability and stronger stability in different task environments. Compared with the probabilistic roadmap-based algorithm and the traditional ant colony algorithm in 10 cases,the improvement in path length optimization can reach 21.13% and 49.31% maximally,and the stability improvement can reach 99.56% and 99.82% maximally.
[1] Rathinam S, Kim Z W, Sengupta R. Vision-based monitoring of locally linear structures using an unmanned aerial vehicle[J]. Journal of Infrastructure Systems,2008, 14(1):52-63.
[2] You Y, Fan Z, Chen W, et al. Design and implementation of mobile manipulator system[C]. The 9th IEEE Annual International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, Suzhou, China, July 29-August 2, 2019.
[3] Hu D, Zhong H, Li S, et al. Segmenting areas of potential contamination for adaptive robotic disinfection in built environments[J]. Building and Environment,2020, 184:107226.
[4]赵晓，王铮，黄程侃，等.基于改进A*算法的移动机器人路径规划[J].机器人，2018, 40(6):903-910.
[5]段碧英，柴肇云，辛子朋，等.基于改进A*算法的矿用机器人救援路径规划及仿真分析[J].太原理工大学学报，2024, 55(2):231-241.
[6] Kuffner Steven, La Valle. RRT-connect:an efficient approach to single-query path planning[C]. ICRA2000:IEEE International Conference on Robotics and Automation, San Francisco, CA, USA, April 24-28,2000.
[7] Mashayekhi R, Idris M Y I, Asisi M H, et al. Informed RRT*-connect:an asymptotically optimal single-query path planning method[J]. IEEE Access, 2020, 8:19842-19852.
[8] Hoang V T, Phung M D, Dinh T H, et al. Reconfigurable multi-UAV formation using angle-encoded PSO[C]. The 15th IEEE International Conference on Automation Science and Engineering(IEEE CASE), Univ British Columbia, Vancouver, Canada, August 22-26,2019.
[9] Gao Y, Wei Z Q, Gong F X, et al. Dynamic path planning for underwater vehicles based on modified artificial potential field method[C]. The Fourth International Conference on Digital Manufacturing&Automation,Qingdao, China, June 29-30, 2013.
[10]袁斌，王伟博，王辉.基于改进的粒子群算法的多目标点路径规划[J].浙江科技学院学报，2022, 34(3):225-232, 284.
[11]姜媛媛，李林，朱文昌.基于ISMA的多点遍历路径规划方法[J].电子测量与仪器学报，2023, 37(3):202-210.
[12] Xu Z, Deng D, Shimada K. Autonomous UAV exploration of dynamic environments via incremental sampling and probabilistic roadmap[J]. IEEE Robotics and Automation Letters, 2021, 6(2):2729-2736.
[13]杨闰，李婧如，贾志昆，等.基于可操作度的移动作业机器人多目标路径规划方法研究[J].控制与决策，2024(7):1-10.
[14]王飞，王红勇.基于Maklink图和遗传算法的改航路径规划方法研究[J].交通运输系统工程信息，2014,4(5):154-160.
[15]孙功武，苏义鑫，顾轶超，等.基于改进蚁群算法的水面无人艇路径规划[J].控制与决策，2021, 36(4):847-856.
[16]张恒，何丽，袁亮，等.基于改进双层蚁群算法的移动机器人路径规划[J].控制与决策，2022, 37(2):303-313.
[17]韩龙，张娜，汝洪芳.人工智能算法原理、技巧及应用[M].北京：清华大学出版社，2022.
[18]沈堤，张仁猛，齐铎，等.基于改进蚁群算法和共用航段的搜索救援通道规划[J].空军工程大学学报，2024, 25(3):48-55.
[19]王麟珠，郑晓斌.智能算法在TSP问题中的应用研究[J].机电技术，2024(2):4-6, 32.
[20] Moscato P. On evolution, seaech, optimization, fenetic algorithms and martial arts:towards memetic algorithms[J]. Caltech Concurrent Computation Program, 1989,826:1-67.
[21] Chen J F, Wu T H. Vehicle routing problem with simultaneous deliveries and pickups[J]. Journal of the Operational Research Society, 2006, 57(5):579-587.
基本信息:
DOI：10.19942/j.issn.2096-5915.2024.04.41
中图分类号:O157.5;TP18
引用信息:
[1]郭浩年,彭星光.基于改进Maklink图的多点遍历路径规划算法[J].无人系统技术,2024,7(04):84-94.DOI:10.19942/j.issn.2096-5915.2024.04.41.
基金信息:
国家自然科学基金（62076203）
2024-05-31
2024
2024-08-06
2024
2024-06-28
1
2024-08-15
2024-08-15