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This paper presents an approach to binocular vision simultaneous localization and mapping (SLAM). SIFT (Scale Invariant Feature Transform) algorithm is used to extract the Natural landmarks, The minimal connected dominating set(CDS) approach is used in data association which solve the problem that the scale of data association increase with the map grows in process of SLAM. Two improvements are introduced...
A new approach to vision-based simultaneous localization and mapping (SLAM) is proposed. the scale invariant feature transform (SIFT) features is landmarks, The minimal connected dominating set(CDS) approach is used in data association which solve the problem that the scale of data association increase with the map grows in process of SLAM . SLAM is completed by fusing the information of binocular...
In this paper, we propose a system which reconstructs the environment with both color and 3D information. We perform extrinsic calibration of a camera and a LRF (laser range finder) to fuse 3D information and color information of objects. We also formularize an equation to measure the result of the calibration. Moreover, we acquire 3D data by rotating 2D LRF with camera, and use ICP (iterative closest...
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