基于IAPF与多层Morphin搜索树的移动机器人路径规划

发布时间：2018-03-31 20:00

本文选题：改进人工势场法　切入点：多层Morphin搜索树算法　出处：《电子测量与仪器学报》2017年02期

【摘要】：针对传统人工势场法(artificial potential field,APF)的易出现振荡、死区、局部极小值等缺陷。提出一种结合机器人位置、速度、加速度及障碍物位置等信息的改进人工势场法(improved artificial potential field,IAPF)。利用Morphin算法计算效率高、易结合全局路径规划算法的优点,提出一种多层Morphin搜索树算法。首先,利用改进人工势场法完成路径的全局规划,在此基础上在障碍物附近用多层Morphin搜索树算法进行路径规划。利用MATLAB仿真测试表明,所提出的改进人工势场法与多层Morphin搜索树的混合算法,在移动机器人自主路径规划中,能有效缩短路径长度,提高到达目标点的效率,高效完成路径规划。
[Abstract]:Aiming at the disadvantages of traditional artificial potential field APF (artificial potential field), such as oscillation, dead zone, local minimum, etc., this paper presents a method of combining the position and velocity of the robot. An improved artificial potential field method based on acceleration and obstacle position is proposed. A multilayer Morphin search tree algorithm is proposed based on the high computational efficiency of the Morphin algorithm and the advantages of the global path planning algorithm. The improved artificial potential field method is used to complete the global path planning, and the multi-layer Morphin search tree algorithm is used to plan the path near obstacles. The MATLAB simulation results show that, The hybrid algorithm of the improved artificial potential field method and multi-layer Morphin search tree can effectively shorten the path length, improve the efficiency of reaching the target point, and efficiently complete the path planning in mobile robot autonomous path planning.
【作者单位】：安徽工程大学安徽省电气传动与控制重点实验室;
【基金】：2016年安微工程大学研究生实践与创新基金(Y040116004)资助项目
【分类号】：TP242

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