基于改进APF-QRRT^(*)策略的移动机器人路径规划  

Path Planning of Mobile Robot Based on Improved APF-QRRT^(*)Strategy

作　　者：刘文浩 余胜东 吴鸿源[1,2] 胡文科 李小鹏 蔡博凡 马金玉 LIU Wenhao;YU Shengdong;WU Hongyuan;HU Wenke;LI Xiaopeng;CAI Bofan;MA Jinyu(College of Mechanical and Electrical Engineering,Wenzhou University,Wenzhou 325000,China;Wenzhou Institute,University of Chinese Academy of Sciences,Wenzhou 325000,China;School of Aeronautics,Nanjing University of Aeronautics and Astronautics,Nanjing 210000,China)

机构地区：[1]温州大学机电工程学院,浙江温州325000 [2]国科温州研究院(温州生物材料与工程研究所),浙江温州325000 [3]南京航空航天大学航空学院,南京210000

出　　处：《电光与控制》2025年第1期21-26,33,共7页Electronics Optics & Control

基　　金：国家自然科学基金面上项目(31971290);温州市科技计划项目(G20240009)。

摘　　要：针对Q-RRT^(*)算法在路径规划过程中无法兼顾可达性和安全性的问题,提出一种改进APF-QRRT^(*)(IAPF-QRRT^(*))路径规划策略。IAPF-QRRT^(*)策略通过Q-RRT^(*)算法获得一组连接起点到终点的离散关键路径点,较传统的快速搜索随机树(RRT^(*))算法具备更好的初始解和更快的收敛速度。改进传统人工势场(APF)方法获得一种新的无势正交向量场,在一定条件下使整体排斥向量场与吸引向量场正交,并将其作用于关键路径点,从而提高路径的安全性。将IAPF-QRRT^(*)策略与其他算法比较,通过数值模拟实验证明了所提策略的有效性。This paper presents an enhanced path planning strategy,namely Improved Artificial Potential Field-QRRT^(*)(IAPF-QRRT^(*)),to address the problem of the existing Q-RRT^(*)algorithm in meeting both reachability and safety requirements during the path planning process.The IAPF-QRRT^(*)strategy utilizes the Q-RRT^(*)algorithm to obtain a set of critical discrete path points that connect the starting and ending points,which offers improved initial solutions and faster convergence speed compared with the traditional RRT^(*)algorithm.Additionally,a novel non-potential orthogonal vector field is derived by enhancing the conventional Artificial Potential Field(APF)method.Under specific conditions,the repulsive vector field is orthogonal to the attractive vector field,thereby enhancing safety along the critical path points.Comparative analysis with other algorithms validates the effectiveness of the proposed IAPF-QRRT^(*)strategy through numerical simulation experiments.

关 键 词：移动机器人 路径规划 人工势场法 Q-RRT^(*)算法 安全性 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]