Most Unmanned Aerial Vehicle (UAV) controllers require linear velocities as input. An effective method to obtain linear velocity is to place a downward facing camera and to estimate the velocity from the optical flow. However, this technique fails in outdoor environments when the ground is covered with grass or other objects which move due to winds such as those caused by the propellers. We present a novel method to estimate the linear velocities from stereo images even in the presence of disorderly motion of image features. We validate the approach using imagery obtained from a UAV flying through orchard rows.
|Original language||English (US)|
|Title of host publication||IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Dec 13 2017|
|Event||2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 - Vancouver, Canada|
Duration: Sep 24 2017 → Sep 28 2017
|Name||IEEE International Conference on Intelligent Robots and Systems|
|Other||2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017|
|Period||9/24/17 → 9/28/17|
Bibliographical noteFunding Information:
This work is supported in part by NSF Award 1317788, USDA Award MIN-98-G02 and the MnDrive. 1W. Dong and V. Isler are with the Department of Computer Science and Engineering, University of Minnesota, Twin Cities, MN, 55455, USA.
This work is supported in part by NSF Award 1317788, USDA Award MIN-98-G02 and the MnDrive.