VISION-BASED TARGET RECOGNITION AND AUTONOMOUS FLIGHTS THROUGH OBSTACLE ARCHES WITH A SMALL UAV
The challenge for unmanned aerial vehicles to sense and avoid obstacles becomes even harder if narrow passages have to be passed for which no precise a-priori position information is available. Inspired by recent UAV flight competitions, this work presents a vision-based approach to search for a narrow gate and to fly through it autonomously. The gate's precise position has to be detected in order to avoid a collision. Using a GPS-based self localization, the camera alignment and the gate position are estimated simultaneously. The presented approach alters a set of waypoints to fly through the gate. All algorithms run onboard the vehicle such that the gate is passed autonomously. Results from flight tests are presented that underline the feasibility of the presented approach.
Published in 2009.