Abstract
We describe a novel quadrotor Micro Air Vehicle (MAV) system that is designed to use computer vision algorithms within the flight control loop. The main contribution is a MAV system that is able to run both the vision-based flight control and stereo-vision-based obstacle detection parallelly on an embedded computer onboard the MAV. The system design features the integration of a powerful onboard computer and the synchronization of IMU-Vision measurements by hardware timestamping which allows tight integration of IMU measurements into the computer vision pipeline. We evaluate the accuracy of marker-based visual pose estimation for flight control and demonstrate marker-based autonomous flight including obstacle detection using stereo vision. We also show the benefits of our IMU-Vision synchronization for egomotion estimation in additional experiments where we use the synchronized measurements for pose estimation using the 2pt+gravity formulation of the PnP problem.
Originalsprache | englisch |
---|---|
Seiten (von - bis) | 21-39 |
Seitenumfang | 19 |
Fachzeitschrift | Autonomous Robots |
Jahrgang | 33 |
Ausgabenummer | 1-2 |
DOIs | |
Publikationsstatus | Veröffentlicht - Aug. 2012 |
ASJC Scopus subject areas
- Artificial intelligence