Robot Obstacle Avoidance and Navigation Control Algorithm Research Based on Multi-Sensor Information Fusion

Abstract

Multi-sensor information fusion technology has very extensive application prospect in robot obstacle avoidance. To solve the problems of robot obstacle avoidance and path scheduling for mobile robots, this article proposes a T-S based FNN multi-sensor information fusion approach integrated with fuzzy logic and neural network. It analyzes the learning algorithm based on gradient in FNN and improved the computing process, which avoids possible oscillation and reduces training time of network. Then the secondary fusion scheme implemented on robot obstacle avoidance and navigation control is designed. The simulations verify that our approach is feasible and effective in obstacle avoidance and path planning for mobile robots.