Robot path planning in dynamic environment based on reinforcement learning

Proposes an adaptive learning method based on reinforcement learning for robot path planning problem, which enables the robot to adaptively learn and perform effective path planning, to avoid the moving obstacles and reach the target. Thereby achieving automatic construction of path planning strategy and making the system adaptive to multi robots system dynamic environments, and concludes from computer simulation experiment that the method is powerful to solve the problem of multi robot path planning, and it is a meaningful try to apply reinforcement learning techniques in multi robot systems to develop the system’s intelligence degree.