TY - JFULL AU - Hsiang-Wen Hsieh and Chin-Chia Wu and Hung-Hsiu Yu and Shu-Fan Liu PY - 2008/6/ TI - A Hybrid Distributed Vision System for Robot Localization T2 - International Journal of Computer and Information Engineering SP - 1741 EP - 1748 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/4482 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 17, 2008 N2 - Localization is one of the critical issues in the field of robot navigation. With an accurate estimate of the robot pose, robots will be capable of navigating in the environment autonomously and efficiently. In this paper, a hybrid Distributed Vision System (DVS) for robot localization is presented. The presented approach integrates odometry data from robot and images captured from overhead cameras installed in the environment to help reduce possibilities of fail localization due to effects of illumination, encoder accumulated errors, and low quality range data. An odometry-based motion model is applied to predict robot poses, and robot images captured by overhead cameras are then used to update pose estimates with HSV histogram-based measurement model. Experiment results show the presented approach could localize robots in a global world coordinate system with localization errors within 100mm. ER -