农业机械学报2017，Vol.48Issue(4)：34-40,102,8.DOI:10.6041/j.issn.1000-1298.2017.04.004
基于动态反馈A*蚁群算法的平滑路径规划方法
Smooth Path Planning Method Based on Dynamic Feedback A* Ant Colony Algorithm
摘要
Abstract
A smooth path planning method for mobile robot with A* ant colony optimization was proposed based on dynamic feedback for mobile robot.First of all,in order to overcome the disadvantage about slow convergence speed of ant colony algorithm,simplified A* algorithm was presented to optimize the initial pheromone settings,which was able to solve the blindness of the first search.In this step,the planning path with the minimum value of the valuation function was obtained by the evaluation function of A* algorithm.And the presented multi-evolutionary strategy mechanism which could increase search space was used to strengthen the global search ability of the algorithm.Secondly,in order to further improve the adaptability of algorithm about the problem of local minimum and stagnation in the path planning,the key parameters of the algorithm were systematically analyzed and the closed-loop feedback idea was adopted to adjust the parameters of ant colony optimization algorithm dynamically.Finally,combining with the Cubic B spline curve method,the planning path was smoothed to meet the practical movement route of mobile robot.The simulation experiment results showed that compared with traditional ant colony (AC),A* ant colony optimization based on dynamic feedback could reduce 10.4％ of the average path cost and shorten 65.8 ％ of the computing time in average.In addition,compared with ant colony system (ACS),the average path cost could be reduced by 5.9％,the calculation time could be shortened by 52.6％.The improved ant colony optimization algorithm could plan a smooth and high quality path in both the dynamic and static environments.关键词
路径规划/蚁群算法/动态反馈/A*算法/B样条曲线Key words
path planning/ant colony algorithm/dynamic feedback/A * algorithm/B spline curve分类
信息技术与安全科学引用本文复制引用
黄辰,费继友,刘洋,李花,刘晓东..基于动态反馈A*蚁群算法的平滑路径规划方法[J].农业机械学报,2017,48(4):34-40,102,8.基金项目
国家自然科学基金项目(51376028)和“十二五”国家科技支撑计划项目(2015BAF20B02) （51376028）
