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空天防御  2024, Vol. 7 Issue (1): 71-80    
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  专业技术 本期目录 | 过刊浏览 | 高级检索 |
一种具有必经点约束的非结构化环境路径规划方法
董德金1,2, 范云锋3, 蔡云泽1,2
1. 上海交通大学 自动化系,上海 200240; 2. 系统控制与信息处理教育部重点实验室,上海 200240; 3. 上海机电工程研究所,上海 201109
Path Planning with Designated-Points Constraints for Unstructured Environment
DONG Dejin1,2, FAN Yunfeng3, CAI Yunze1,2
1. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240,China; 2. Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240,China; 3. Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109,China
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摘要 针对非结构化环境下具有必经点约束的路径规划问题,设计一种两阶段求解方法,并对每一阶段算法做出改进。第1阶段,对典型非结构化环境进行地图建模,针对A-Star算法存在的接触障碍物、路径曲折的问题,提出新的障碍物安全距离方法并设计折线优化策略平滑路径。第2阶段,详细阐述必经点问题的求解流程,建模为旅行商变体问题并将多种优化算法拓展至必经点场景。由于现有方法难以高效求解必经点问题,提出一种改进遗传粒子群(IGPSO)算法,包括分层随机初始化、改进交叉方式以及变异算子。最后进行对比实验验证,结果表明改进算法在最优解成功率、运行时间和迭代次数方面具备明显优势。
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关键词 路径规划必经点A-Star算法遗传粒子群算法    
Abstract:Focusing on path planning with designated point constraints in unstructured environments, this study has proposed a two-stage solution method which can improve the algorithm for each stage. In the first stage, map modelling was commissioned on typical unstructured environments. To solve the problems of contacting obstacles and winding paths in the A-Star algorithm, a new obstacle safety distance method was established and a line optimization strategy was developed to smooth the path. In the second stage, the processes of solving the designated-points problem were elaborated in detail, modelling a travel salesman variant problem and extending various optimization algorithms to this scenario. Due to the existing methods’ difficulty in effectively solving designated-point problems, an improved Genetic Particle Swarm Optimization (IGPSO) algorithm was proposed, including a hierarchical random initialization, an improved crossover method, and a mutation operator. Finally, comparative experiments were conducted where the significant advantages of the improved algorithm in optimal solution success rate, running time, and number of iterations were verified.
Key wordspath planning    designated-points    A-Star algorithm    genetic particle swarm optimization algorithm
收稿日期: 2023-10-25      出版日期: 2024-03-05
ZTFLH:  TP 242  
基金资助:中国航天科技集团有限公司第八研究院产学研合作基金(USCAST2022-11)
作者简介: 董德金(2000—),男,硕士研究生。
引用本文:   
董德金, 范云锋, 蔡云泽. 一种具有必经点约束的非结构化环境路径规划方法[J]. 空天防御, 2024, 7(1): 71-80.
DONG Dejin, FAN Yunfeng, CAI Yunze. Path Planning with Designated-Points Constraints for Unstructured Environment. Air & Space Defense, 2024, 7(1): 71-80.
链接本文:  
https://www.qk.sjtu.edu.cn/ktfy/CN/      或      https://www.qk.sjtu.edu.cn/ktfy/CN/Y2024/V7/I1/71

参考文献
[1] 李昭莹, 欧一鸣, 石若凌. 基于深度Q网络的改进RRT路径规划算法[J]. 空天防御, 2021, 4(3): 17-23.
[2] 李征, 陈建伟, 彭博. 基于伪谱法的无人机集群飞行路径规划[J]. 空天防御, 2021, 4(1): 52-59.
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