| 单子豪1,2, 俞建峰1,2*, 钱陈豪1,2.基于A*与APF融合算法的移动机器人路径规划[J].轻工机械,2025,43(6):69-78 |
| 基于A*与APF融合算法的移动机器人路径规划 |
| Path Planning of Mobile Robots Based on Fusion of Improved A* and APF Algorithms |
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| DOI:10.3969/j.issn.1005 2895.2025.06.010 |
| 中文关键词: 移动机器人 路径规划 仓储 A*算法 人工势场法 |
| 英文关键词:移动机器人 路径规划 仓储 A*算法 人工势场法 |
| 基金项目:国家自然科学基金(51905215);江苏省研究生科研与实创新计划(SJCX24_1348)。 |
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| 中文摘要: |
| 为了解决仓储环境中搬运机器人寻路时间长、遍历节点数和拐点数较多等问题,针对不同的障碍物环境,笔者提出了一种融合A*算法与人工势场(Artificial Potential Field,APF)法的分层路径规划策略。在全局路径规划阶段,在A*算法的启发函数中引入APF的斥力因子,以增强对障碍物的感知能力,从而生成更安全、平滑的路径;在局部路径执行阶段,采用APF方法实时计算引力和斥力,动态调整机器人轨迹,实现对动态障碍物的有效避让。仿真结果表明:在2种不同的环境下,A* APF算法相比于A*算法,搜索节点数分别减少了54%和27%,搜索时间分别减少了54%和44%,拐点数分别减少了67%和75%,路径长度分别减少了3%和5%。在真实障碍物环境的试验中,A* APF算法路径长度和搜索时间均较小,且始终保持安全结果。 |
| 英文摘要: |
| To address the problems of long path planning time, excessivenumber of traversed nodes and numerous turns of handling robots in warehouse environments, a hierarchical path planning strategy that integrates the A* algorithm with the Artificial Potential Field (APF) algorithm was proposed by author for different obstacle environments. In the global path planning stage, a repulsive factor from the APF was incorporated into the heuristic function of the A* algorithm to enhance obstacle awareness, generating safer and smoother paths. In the local path execution stage, the APF algorithm was used to dynamically calculate attractive and repulsive forces in real time, allowing the robot to effectively avoid dynamic obstacles. Simulation results show that in two different environments,compared with the A* algorithm, the A* APF algorithm reduces the number of searched nodes by 54% and 27%respectively, reduces the search time by 54% and 44%respectively, reduces the number of inflection points by 67% and 75%respectively and reduces the path length by 3% and 5% respectively. In the experiment of real obstacle environment, the path length and search time of A* APF algorithm are small, and the safety results are always maintained. |
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