伍永健,陈跃东,陈孟元.改进QPSO和Morphin算法下移动机器人混合路径规划[J].电子测量与仪器学报,2017,31(2):295-301
改进QPSO和Morphin算法下移动机器人混合路径规划
Hybrid path planning of mobile robot based on improved QPSO and Morphin algorithm
  
DOI:10.13382/j.jemi.2017.02.019
中文关键词:  复杂环境  移动机器人  障碍物  改进QPSO  Morphin算法  混合路径规划
英文关键词:complex environment  mobile robot  obstacle  improved QPSO  Morphin algorithm  hybrid path planning
基金项目:2016年度安徽高校自然科学项目(KJ2016A794)、2016年安徽工程大学研究生实践与创新基金(Y040116004)资助项目
作者单位
伍永健 安徽工程大学安徽省电气传动与控制重点实验室芜湖241000 
陈跃东 安徽工程大学安徽省电气传动与控制重点实验室芜湖241000 
陈孟元 安徽工程大学安徽省电气传动与控制重点实验室芜湖241000 
AuthorInstitution
Wu Yongjian Anhui Polytechnic University, Anhui Key Laboratory of Electric Drive and Control, Wuhu 241000, China 
Chen Yuedong Anhui Polytechnic University, Anhui Key Laboratory of Electric Drive and Control, Wuhu 241000, China 
Chen Mengyuan Anhui Polytechnic University, Anhui Key Laboratory of Electric Drive and Control, Wuhu 241000, China 
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中文摘要:
      为了提高机器人在复杂环境下路径规划的能力,提出了一种基于改进量子粒子群优化算法(QPSO)和Morphin算法的混合路径规划方法。利用栅格地图建立环境模型并确定起始点和目标点,通过引入自适应局部搜索策略和交叉操作对QPSO进行改进规划出一条最优的全局路径,机器人根据全局路径行走,当发现未知静态或动态障碍物立即调用Morphin算法进行局部路径规划,避开障碍物后回到原全局路径上继续行走至目标点。该混合路径规划方法的有效性和可行性通过Matlab仿真和实际应用得到很好地验证。
英文摘要:
      To improve the ability of robot path planning in complex environment, a hybrid path planning method based on improved QPSO and Morphin algorithm is proposed. Firstly, using grid map establishes the environmental model and determines the starting point and the target point. Through the introduction of adaptive search strategy and crossover operation, the QPSO algorithm is improved to plan an optimal global path, the robot is walking according to the global path. When the unknown or dynamic obstacles are found, the Morphin algorithm is used to carry out the local path planning to avoid the obstacles and return to the original global path to continue walking for the target point. The simulation of Matlab and practical application verify the effectiveness and feasibility of the hybrid path planning method.
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