Abstract
An iterative bias estimation framework is presented that mitigates position-dependent ranging errors often present in ultra-wideband localization systems. State estimation and control are integrated, such that the positioning accuracy improves over iterations. The framework is experimentally evaluated on a quadcopter platform, resulting in improvements in the tracking performance with respect to ground truth, and also smoothing the overall flight by significantly reducing unwanted oscillations; see https://youtu.be/J-htfbzf40U for a video.
Original language | English |
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Pages (from-to) | 1391-1396 |
Journal | IFAC-PapersOnline |
Volume | 53 (2020) |
Issue number | 2 |
DOIs | |
Publication status | Published - 2021 |
Event | 21st IFAC World Congress 2020 - Berlin, Germany Duration: 12 Jul 2020 → 17 Jul 2020 |
Keywords
- Adaptive observer design
- Bayesian methods
- Classification
- Iterative and repetitive control
- Recursive least squares
- Sensor fusion
- Ultra-wideband technology