Extended strong tracking filter SLAM algorithm

Simultaneous Localization and Mapping (SLAM) is a key issue in robotics community. This paper presents a monocular vision and odometer based SLAM algorithm, making use of a novel artificial landmark which is called MR (Mobile Robot) code. During robot motion, the information from visual observations is fused with that from the odometer by Extended Strong Tracking Filter (STF), which can construct highly accurate maps and locate the robot more accurately than EKF. A new calculation method of suboptimal multiple fading factors is proposed which overcomes the problem of discontinuous observation in normal STF SLAM. Actual experiments are carried out in indoor environment, which shows that the proposed algorithm has improved the localization precision of the robot and the map accuracy.