Direct feature correspondence in vision-aided inertial navigation for unmanned aerial vehicles
| Autor: | Eric N. Johnson, Daniel Magree, Federico Paredes Valles |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Feature extraction Navigation system 02 engineering and technology Visualization Extended Kalman filter 020901 industrial engineering & automation Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Measurement uncertainty 020201 artificial intelligence & image processing Computer vision Minification Artificial intelligence business Inertial navigation system |
| Zdroj: | 2017 International Conference on Unmanned Aircraft Systems (ICUAS). |
| DOI: | 10.1109/icuas.2017.7991446 |
| Popis: | This paper proposes a novel method for corresponding visual measurements to map points in a visual-inertial navigation system. The algorithm is based on the minimization of the photometric error on sparse locations of the image region, and realizes a gain in robustness that comes from the elimination of the need of feature-extraction for correspondence. The system is compared to a standard approach based on feature extraction, within a visual-inertial EKF formulation. High-fidelity simulation results show the proposed method improves the horizontal RMS error by means of increasing the number of features corresponded by the algorithm. |
| Databáze: | OpenAIRE |
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