Abstract
The authors aim at map based outdoor navigation of a mobile robot. In navigation, robot position is fundamentally obtained by odometry. However, the position is misaligned as the robot moves because odometry has cumulative error. DGPS measurement data may cancel its position error. The framework of EKF is used for the modification and the fusion between odometry and DGPS measurement data. The DGPS measurement data, however, could have large error because of multipath near buildings. In this paper, the authors propose a method which eliminates erroneous DGPS measurement data when odometry robot position is fused, and confirm the validity of this approach.
| Original language | English |
|---|---|
| Pages (from-to) | 1978-1984 |
| Number of pages | 7 |
| Journal | Proceedings - IEEE International Conference on Robotics and Automation |
| Volume | 2 |
| Publication status | Published - Dec 9 2003 |
| Event | 2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan, Province of China Duration: Sept 14 2003 → Sept 19 2003 |
Keywords
- DGPS
- EKF
- Likelihood
- Mobile robot
- Navigation
- Odometry
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering