Name
Abstract | ||
|---|---|---|
We propose a framework for Google Map aided UAV navigation in GPS-denied environment. Geo-referenced navigation provides drift-free localization and does not require loop closures. The UAV position is initialized via correlation, which is simple and efficient. We then use optical flow to predict its position in subsequent frames. During pose tracking, we obtain inter-frame translation either by motion field or homography decomposition, and we use HOG features for registration on Google Map. We employ particle filter to conduct a coarse to fine search to localize the UAV. Offline test using aerial images collected by our quadrotor platform shows promising results as our approach eliminates the drift in dead-reckoning, and the small localization error indicates the superiority of our approach as a supplement to GPS. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ROBIO.2015.7418753 | 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) |
Keywords | DocType | Volume |
Google Map aided UAV visual navigation,UAV,GPS-denied environment,geo-referenced navigation,drift-free localization,UAV position initialization,optical flow,position prediction,pose tracking,interframe translation,motion field,homography decomposition,HOG features,image registration,particle filter,coarse-to-fine search,aerial images,quadrotor platform,dead-reckoning,localization error,unmanned aerial vehicles | Journal | abs/1703.10125 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mo Shan | 1 | 23 | 2.79 |
| Fei Wang | 2 | 18 | 4.15 |
| Feng Lin | 3 | 118 | 17.27 |
| Zhi Gao | 4 | 33 | 10.15 |
| Ya Z. Tang | 5 | 0 | 0.34 |
| Ben M. Chen | 6 | 994 | 131.58 |