Name
Abstract | ||
|---|---|---|
We propose a novel path planning method considering pose errors for off-road mobile robots based on 3D terrain map information. Mobile robots navigating on rough terrain cannot follow a planned path perfectly because of uncertainties such as pose errors. In this work, we represent such pose errors as error ellipsoids to use on collision check with obstacles in a map. The error ellipsoids are estimated based on extended Kalman filter (EKF) that integrates motion errors and global positioning systems (GPS) observation errors. Simulation and experiment results show that the proposed method enables mobile robots to generate a robust path against pose errors in a large-scale rough terrain map. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-01370-7_3 | IAS |
Field | DocType | Citations |
Motion planning,Computer vision,Extended Kalman filter,Ellipsoid,Computer science,Terrain,Collision,Artificial intelligence,Sampling (statistics),Global Positioning System,Mobile robot | Conference | 0 |
PageRank | References | Authors |
0.34 | 5 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuki Doi | 1 | 0 | 0.34 |
| Yonghoon Ji | 2 | 19 | 7.41 |
| Yusuke Tamura | 3 | 56 | 22.73 |
| Yuki Ikeda | 4 | 8 | 4.40 |
| Umemura, A. | 5 | 3 | 1.44 |
| Yoshiharu Kaneshima | 6 | 0 | 0.34 |
| Hiroki Murakami | 7 | 0 | 0.34 |
| Atsushi Yamashita | 8 | 12 | 11.09 |
| Hajime Asama | 9 | 826 | 237.10 |