改进QPSO和Morphin算法下移动机器人混合路径规划

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。

Hybrid path planning of mobile robot based on improved QPSO and Morphin algorithm

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.