Name
Abstract | ||
|---|---|---|
To improve the reliability of perception, autonomous mobile robots often obtain environmental information from multiple sensors. However, the redundancy of sensors and extra fusion process increase the risks of system failure. In this paper, a fault-tolerance architecture is proposed for mobile robot localization and a differential drive mobile robot is investigated. In the architecture, the relative/absolute localization methods are fused by Extended Kalman Filters (EKFs). Furthermore, fault detection and fault identification are accomplished by comparing the outputs of redundancy of fusing processes. Finally, the effectiveness of the fault-tolerance architecture is verified in several experiments conducted in the robot prototype. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICCA.2019.8899574 | 2019 IEEE 15th International Conference on Control and Automation (ICCA) |
Keywords | Field | DocType |
fault tolerant architecture,mobile robot localization,autonomous mobile robots,multiple sensors,fusion process,differential drive mobile robot,fault detection,fault identification,robot prototype,extended Kalman filters | Differential (mechanical device),Architecture,Fault tolerant architecture,Fault detection and isolation,Kalman filter,Real-time computing,Control engineering,Redundancy (engineering),Engineering,Robot,Mobile robot | Conference |
ISSN | ISBN | Citations |
1948-3449 | 978-1-7281-1165-0 | 0 |
PageRank | References | Authors |
0.34 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zuoquan Zhao | 1 | 0 | 0.34 |
| Jiadong Wang | 2 | 0 | 0.34 |
| Jiawei Cao | 3 | 4 | 4.60 |
| Wenchao Gao | 4 | 0 | 0.34 |
| Qinyuan Ren | 5 | 36 | 11.03 |