基于状态改变的机器人路径规划算法

为了解决目前机器人路径规划中时效性低、避障解算量大的问题,借鉴直流电路中理想电感元件两端电压能够从感抗状态恢复到稳定状态的现象,提出了一种利用机器人状态检测量对机器人状态实时检测,从而实现避障的机器人路径规划算法.首先对绕行单个固定障碍物的机器人进行深入分析,然后采用状态叠加的方法,生成任意位置多障碍物同时存在的避障路径.同时对斥力系数进行改进,以确保机器人能够有效到达目标点.为了验证算法在多障碍物环境下的路径规划能力,进行了数值仿真模拟实验.仿真结果表明,使用该算法规划机器人路径时,能够在避免局部极小值点和目标不可达问题的前提下,在较短时间内规划出机器人由起始点到目标点的路径.

Robot Path Planning Algorithm Based on State Change

In order to solve the problems of low timeliness and a large amount of obstacle avoidance solution in current robot path planning, a robot path planning algorithm is proposed, which is based on the phenomenon that the voltage at both ends of ideal inductance element in DC circuit can recover from inductive reactance state to stable state. Firstly, the robot around a single fixed obstacle is analyzed in depth, and then the method of state superposition is used to generate the obstacle avoidance path with multiple obstacles at any location.At the same time, the repulsion coefficient is improved to ensure that the robot can reach the target point effectively.In order to verify the path planning ability of the algorithm under multi-obstacle condition, the numerical simulation experiment has been done. The simulation results show that, when using the algorithm to plan the robot path, the path from the starting point to the target point can be planned in a short time without the local minimum point and the target unreachable problem.