Image features-based mobile robot visual SLAM

Accurate localization and mapping play a pivotal role in mobile robot navigation. In this paper, we present a novel algorithm for mobile robot SLAM (Simultaneous Localization and Mapping) based on stereo vision. First a novel method is proposed to extract distinctive invariant image features, which is coined PLOT (Polynomial Local Orientation Tensor). The stability of these features to image translation, scaling, rotation and illumination changes makes them suitable landmarks for mobile robot visual SLAM. The visual landmarks relative to the robot can be established by matching the PLOT features. Mobile robot localization is achieved by matching these distinctive landmarks in the current frame to the database map. RANSAC algorithm is improved, coined extended RANSAC, for mobile robot pose estimate due to its efficiency. Meanwhile, the visual landmarks in the database map are updated correspondingly. Experimental results show that the proposed method based on the PLOT features achieves SLAM for mobile robot with higher precision.