Path planning obstacle avoidance auxiliary method based on reinforcement learning

The invention discloses a path planning obstacle avoidance auxiliary method based on reinforcement learning. The method comprises the following steps of S1, building a mobile robot model, and carryingout the path planning from a starting point to a target point based on a Q learning algorithm, and S2, when the mobile robot is detected to be currently at the local optimal point, determining a temporary target point, changing the target point into the temporary target point, and performing path planning based on a Q learning algorithm by taking the current position as a starting point and the temporary target point as the target point so as to move to the direction of the temporary target point. 本发明公开了一种基于强化学习的路径规划避障辅助方法，包括如下步骤：步骤S1，构建移动机器人模型，基于Q学习算法对起点到目标点进行路径规划；步骤S2，当检测到移动机器人当前处于局部最优点时，确定临时目标点，将所述目标点更改为临时目标点，并以当前位置为起点，所述临时目标点为目标点，基于Q学习算法进行路径规划，以向临时目标点方向移动。