Abstract
This paper presents both the theory and the first experimental results of a new method which allows simultaneously estimating of the robot configuration and the odometry error (both systematic and non-systematic) during the mobile robot navigation. The estimation of the non-systematic components is carried out through an augmented Kalman filter which estimates a state containing the robot configuration and the parameters characterizing the systematic component of the odometry error. It uses encoder readings as inputs and the readings from a laser range finder as observations. The estimation of the non-systematic component is carried out through another Kalman filter where the observations are obtained by two subsequent robot configurations provided by the previous augmented Kalman filter.
| Original language | English |
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| Pages | 1499-1504 |
| Number of pages | 6 |
| Publication status | Published - 26 Dec 2003 |
| Externally published | Yes |
| Event | 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States Duration: 27 Oct 2003 → 31 Oct 2003 |
Conference
| Conference | 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems |
|---|---|
| Country/Territory | United States |
| City | Las Vegas, NV |
| Period | 27/10/03 → 31/10/03 |
Keywords
- Kalman filter
- Odometry Learning
- Robot Navigation