Abstract
State estimation in dynamical telepresence systemsis very important in real-world applications as the true state of the robot is unspecified and sensors provide only a sequence of noisy measurements. In this research, we proposed a new technique of state estimation using delayed sensor measurements of a Telepresence robot for real-time navigation. An Augmented State Extended Kalman Filter (AS-EKF) is introduced to estimate the true position of the robot. The proposed algorithm was successfully tested in a real-environment experimental frameworkusing a state-of-the-art differential-drive telepresence robot. Our results show improvements of an average of more than 34% when compared to traditional EKF.
| Original language | English |
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| Title of host publication | Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019 |
| Place of Publication | Piscataway, NJ |
| Publisher | IEEE |
| Pages | 624-629 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538692455 |
| ISBN (Print) | 9781538692455 |
| DOIs | |
| Publication status | Published - 26 Mar 2019 |
| Event | The Third IEEE International Conference on Robotic Computing - Naples, Italy Duration: 25 Feb 2019 → 27 Feb 2019 |
Conference
| Conference | The Third IEEE International Conference on Robotic Computing |
|---|---|
| Abbreviated title | IRC 2019 |
| Country/Territory | Italy |
| City | Naples |
| Period | 25/02/19 → 27/02/19 |
Keywords
- state estimation
- EKF
- augmented state
- telepresence
- robot navigation
- time delay