摘要
针对蚁群算法在机器人路径规划过程中存在的收敛速度慢、效率较低、容易陷入局部最优等缺点,提出了一种多步长的改进蚁群算法.该算法实现了多步长路径规划;同时在概率公式中加入了拐点参数,使路径更加平滑;并且提出了新的信息素奖励惩罚机制.将改进的蚁群算法应用于具有3个优化目标的多机器人路径规划中,采用碰撞预测策略和路径协调策略完成多机器人间的协调避碰.仿真结果表明,改进的蚁群算法规划的路径更短、更平滑,效率更高,验证了该算法在多机器人路径规划中的有效性和可行性.
The basic ant colony algorithm has problems of slow convergence speed, inefficiency and easy to fall into local optimization in the process of robot path planning.Aiming at these problems,an improved ant colony algorithm is proposed.Multi-step path planning is realized by this proposed algorithm. In order to make the path smoother, the inflection point is added in the probability formula. This article proposed a new pheromone reward punishment mechanism. The improved ant colony algorithm is applied to the multi-robot path planning with three optimization goals. Collision prediction strategy and path coordination strategy is applied to solve the problem of coordination and obstacle avoidance between mobile robots. The simulation results show that the path planned by improved ant colony algorithm is shorter, smoother and more efficient, which verifies the effectiveness and feasibility of the proposed algorithm in multi robot path planning.
作者
顾军华
孟慧婕
夏红梅
董永峰
GU Junhua MENG Huijie XIA Hongmei DONG Yongfeng(School of Computer Science and Engineering, Hebei University of Technology, Tianjin 300401, China Hebei Province Key Laboratory of Big Data Calculation, Tianjin 300401, China Editorial Department of Journal of Hebei University of Technology, Hebei University of Technology, Tianjin 300401, China)
出处
《河北工业大学学报》
CAS
2016年第5期28-34,共7页
Journal of Hebei University of Technology
基金
天津市应用基础与前沿技术研究计划(13JCQNJC00200
14JCYBJC18500)
河北省高等学校科学技术研究项目(ZD20131097)
河北省自然科学基金(F2015202311)
关键词
多机器人
路径规划
改进蚁群算法
多步长
拐点参数
协调避碰
multi-robot
path planning
improved ant colony algorithm
multi-step
inflection point parameter
coordinated collision avoidance
