基于改进蚁群算法的移动机器人动态路径规划  被引量:11

Mobile robot dynamic path planning based on improved ant colony algorithm

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作  者:任红格 胡鸿长 史涛 REN Hongge;HU Hongchang;SHI Tao(College of Electrical Engineering,North China University of Science and Technology,Tangshan 063210,China)

机构地区:[1]华北理工大学电气工程学院,河北唐山063210

出  处:《现代电子技术》2021年第20期182-186,共5页Modern Electronics Technique

基  金:国家自然科学基金项目(61203343);河北省自然科学基金项目(F2018209289)。

摘  要:针对动态环境下移动机器人路径规划问题,提出一种全局路径规划与局部路径规划相结合的二次规划方法。首先基于静态环境先验知识提出一种改进蚁群算法。在基本蚁群算法的基础上,修改蚂蚁路径搜索策略来跳出部分特殊形状障碍物;修改基本蚁群算法概率选择公式中的启发函数,将目标节点信息加入启发函数中,加速算法收敛;修改基本蚁群算法概率选择公式中的挥发系数,将时间和空间信息加入挥发系数中,提高算法的自适应性。在规划过程中,通过分析动态障碍物运动情况,针对障碍物不同运动状态提出相应的避碰策略。仿真实验表明,所提算法优于基本蚁群算法,而且能够有效实现机器人在动态环境中的避障目标,获得无碰最优或次优路径。A quadratic planning method combining global path planning and local path planning is proposed to realize mobile robot path planning in dynamic environment.Firstly,an improved ant colony algorithm is proposed on the basis of prior knowledge of static environment.On the basis of the basic ant colony algorithm,the ant path search strategy is modified to make the robot jump out some special shape obstacles the heuristic function in the basic ant colony algorithm probability selection formula is modified by adding the target node information to it to accelerate the algorithm convergence.The volatilization coefficient in the probability selection formula of basic ant colony algorithm is modified by adding time and space information to it to improve the adaptability of the algorithm.In the planning process,by analyzing the motion of dynamic obstacles,the corresponding collision avoidance strategy is proposed for different motion states of obstacles.The simulation results show that the proposed algorithm is superior to the basic ant colony algorithm,and can effectively achieve the obstacle avoidance of the robot in the dynamic environment,and obtain the optimal or suboptimal path without collision.

关 键 词:移动机器人 路径规划 动态环境 蚁群算法 启发函数修改 机器人避障 

分 类 号:TN820.4-34[电子电信—信息与通信工程] TP391[自动化与计算机技术—计算机应用技术]

 

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