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| Omni-vision and Odometer Based Self-localization for Mobile Robot |
| WANG Jing-chuan1, CHEN Wei-dong1, CAO Qi-xin2 |
1. Institute of Automation, Shanghai Jiaotong University, Shanghai 200030;
2. Institute of Robotics, Shanghai Jiaotong University, Shanghai 200030, China |
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Abstract By analyzing the uncertainties in perception models of omni-vision and odometer systems for mobile robot, a landmark-observation-based self-localization method with Kalman filter is proposed, which fuses the data from multiple sensors at successive observation points. Compared with single-sensor methods, it exploits the differences in uncertainty between omni-vision and odometer systems, and consequently improves the self-localization precision of mobile robot. The experimental results show the validity and feasibility of the proposed method.
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Received: 20 June 2004
Published: 15 January 2005
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