Obstacle Detection Based on Heterogeneous Data Fusion

Abstract

Obstacle detection is very important for the autonomous movement of robots. Variety of sensors are used in obstacle detection to obtain information about obstacles. Different types of data obtained by sensors cannot be directly analyzed. This paper proposed an obstacle detection method based on heterogeneous data fusion. An image processing method is adopted to process the image of obstacle obtained by monocular vision sensor, and the size and position of the obstacle can be obtained. Then using infrared distance sensors are used to obtain distance of obstacles. Finally the location and distance information of obstacles can be obtained by a specific algorithm. Two experiments are performed for verifing the effect of proposed method. Experiments shown that the proposed method can effectively obtain the position and distance of obstacles.