Path Planning System for the Aerial Work Robot with Self-Propelled

The Aerial Work Robot with Self-propelled is mainly used outdoors. The robot can replace high-altitude work platforms to a certain extent and perform maintenance and repair tasks for municipal projects and other routine projects. When the robot enters the operation area, it needs to walk and rise according to the established route, and prevent collision with surrounding objects in the course of operation and cause accidents. In this paper, the robot's driving path and work path are planned based on fuzzy logic control and reinforcement learning according to the operational requirements of robot. The reinforcement learning theory about anti-collision of robot is used to analyze the collision factors in the robot's driving process and the operation process. And then the robot can realize the ability of avoiding the risk factors automatically by the algorithms and achieves the safe walking and operation.