Landing a rotorcraft unmanned aerial vehicle (RUAV) without human supervision is a capability that would significantly broaden the usefulness of UAVs. The benefits are even greater if the functionality is expanded to involve landing sites with unknown terrain and a lack of GPS or other positioning aids. Examples of these types of non-cooperative environments could range from remote mountainous regions to an urban building rooftop or a cluttered parking lot. The research of this thesis builds upon an approach that was initiated at NASA Ames Research Center to advance technology in the landing phase of RUAV operations. The approach consists of applying JPL's binocular stereo ranging algorithm to identify a landing site free of hazardous terrain. JPL's monocular feature tracking algorithm is then applied to keep track of the chosen landing point in subsequent camera images. Finally, a position-estimation routine makes use of the tracking output to estimate the rotorcraft's position relative to the landing point. These position estimates make it possible to guide the rotorcraft toward, and land at, the safe landing site. This methodology is implemented in simulation within the context of a fully-autonomous RUAV mission. Performance metrics are defined and tests are carried out in simulation to independently evaluate the performance of each algorithm. The stereo ranging algorithm is shown to successfully identify a safe landing point on average 70%-90% of the time in a cluttered parking lot scenario. The tracking algorithm is demonstrated to be robust under extreme operating conditions, and lead to a position-estimation error of less than 1 meter during a 2-minute hover at 12 meters above the ground. Preliminary tests with actual flight hardware are done to confirm the validity of these results, and to prepare for demonstrations and testing in flight.
College and Department
Ira A. Fulton College of Engineering and Technology; Mechanical Engineering
BYU ScholarsArchive Citation
Rowley, Dale D., "Real-time Evaluation of Vision-based Navigation for Autonomous Landing of a Rotorcraft Unmanned Aerial Vehicle in a Non-cooperative Environment" (2005). All Theses and Dissertations. 248.
autonomous, uav, landing, vision-based, navigation