Motion Route Planning and Obstacle Avoidance Method for Mobile Robot Based on Deep Learning

Abstract

In order to improve the motion route planning effect and obstacle avoidance effect of mobile robots, this paper combines the deep learning theory to analyze the motion route planning and obstacle avoidance process of mobile robots. According to the obstacle avoidance trajectory and constraints, this paper establishes a safe distance model for obstacle avoidance, then analyzes the braking process of the robot, and designs an improved safety model for obstacle avoidance. This model integrates two relatively mature safety models, complements their advantages and disadvantages, and comprehensively considers robot safety and the utilization of the motion path. According to the simulation test research, the robot based on deep learning proposed in this paper has a good motion route planning effect and obstacle avoidance effect and can effectively improve the autonomous motion effect of the robot.