Obstacle avoidance research of snake-like robot based on multi-sensor information fusion

The snake-like robot needs to adapt to complex environment, in order to reach the target point safely and collisionless, necessary obstacle avoidance strategy is of vital importance. In this paper, laser radar and ultrasonic sensors are used to detect the surrounding environment, and then information fusion method based on TS fuzzy neural network is adopted to integrate the collected information, which provides the necessary condition for obstacle avoidance research of the snake-like robot. Experiments show that the snake-like robot can successfully avoid obstacles to reach the target point after training of the fuzzy neural network.