基于IAPF与多层Morphin搜索树的移动机器人路径规划

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。

Mobile robot path planning based on IAPF and multilayer Morphin searching tree

Aiming at the imperfections of traditional artificial potential field (APF) method such as vibration, dead zone, local minimum, improved artificial potential field (IAPF) method with a combination of robot position, speed, accelerated speed, and obstacles' position is presented.Taking advantage of the Morphin algorithm, which is high efficiency and easy to combine the global path planning algorithm, multilayer Morphin search tree algorithm is presented.First, IAPF method is used to complete the path of global planning.On this basis, the multilayer Morphin searching tree algorithm is used for path planning nearby obstacle.MATLAB simulation tests show that the mixed algorithm with IAPF and multilayer Morphin search tree algorithm can effectively shorten the path length and improve the efficiency to reach the target in the autonomous mobile robot path planning, efficiently complete path planning.