A multi-sensor fusion SLAM approach for mobile robots
The ability to simultaneously localize a robot and accurately map its surroundings is considered to be key prerequisite of truly autonomous robots. This paper presents a novel method, which enhances the use of external mechanisms by considering a multi-sensor system, composed of sonar and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensor. Hough transform is utilized to extract features from raw sonar data and vision image. The information is fused at the level of features. This technique improves the reliability significantly and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.