A SLAM Model Based on Omni-Directional Vision and Odometer
A new SLAM measurement model based on omnidirectional vision and odometer is proposed in this paper. A virtual stereo vision composed of an omnidirectional vision sensor and an odometer. Scale Invariant Feature Transform is used to extract stable and available vision features from the omni-images. The 3-D locations of these features are initialized by the pixel coordinates and the odometer data by stereo projection, and the locations will be corrected during the SLAM process when they are observed again. It is demonstrated that the new model can make a good accuracy with FastSLAM algorithm, and the accuracy is greatly improved corresponding to the classical vision sensor.
Mobile robot SLAM, SIFT measurement model omni-directional vision
Wang Yuquan Li Yinghong
College of Mechanical Electronical and Engineering, North China University of Technology, Beijing,China
国际会议
湘潭
英文
128-133
2011-07-19（万方平台首次上网日期，不代表论文的发表时间）