@inproceedings{c3208494550a4914a39470542e4fb9d1,
title = "Online calibration for monocular vision and odometry fusion",
abstract = "A novel calibration approach for mobile robot equipped with encoder and monocular camera has been proposed in this paper. In this work, we divide the calibration into four steps: 1) a coarse calibration step is employed to estimate the transform between odometry and visual system and the scale of visual system; 2) a nonlinear-optimization step is employed to optimize the transform between odometry and visual system; 3) during the process of SLAM of mobile robot, the transform between odometry and visual system is optimized with the poses of mobile robot and positions of mappoints in a local map; 4) the scale of visual system is optimized after a loop detection. This method uses only nature features in visual system without any artificial landmark or any prior knowledge. The experiment and compare have been performed to illustrate the effectiveness.",
keywords = "Calibration, Sensor Fusion",
author = "Xuefeng Wang and Haoyao Chen and Yanjie Li",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Unmanned Systems, ICUS 2017 ; Conference date: 27-10-2017 Through 29-10-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICUS.2017.8278415",
language = "英语",
series = "Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "602--607",
editor = "Xin Xu",
booktitle = "Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017",
address = "美国",
}