Real-time Evaluation of Vision-based Navigation for Autonomous Landing of a Rotorcraft Unmanned Aerial Vehicle in a Non-cooperative Environment Real-time Evaluation of Vision-based Navigation for Autonomous Landing of a Rotorcraft Unmanned Aerial Vehicle in a Non-cooperative Environment
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.
School:Brigham Young University
School Location:USA - Utah
Source Type:Master's Thesis
Keywords:autonomous uav landing vision based navigation
Date of Publication:02/28/2005