Title
Vision-based landing site evaluation and informed optimal trajectory generation toward autonomous rooftop landing
Abstract
Autonomous landing is an essential function for micro air vehicles (MAVs) for many scenarios. We pursue an active perception strategy that enables MAVs with limited onboard sensing and processing capabilities to concurrently assess feasible rooftop landing sites with a vision-based perception system while generating trajectories that balance continued landing site assessment and the requirement to provide visual monitoring of an interest point. The contributions of the work are twofold: (1) a perception system that employs a dense motion stereo approach that determines the 3D model of the captured scene without the need of geo-referenced images, scene geometry constraints, or external navigation aids; and (2) an online trajectory generation approach that balances the need to concurrently explore available rooftop vantages of an interest point while ensuring confidence in the landing site suitability by considering the impact of landing site uncertainty as assessed by the perception system. Simulation and experimental evaluation of the performance of the perception and trajectory generation methodologies are analyzed independently and jointly in order to establish the efficacy and robustness of the proposed approach.
Year
DOI
Venue
2015
10.1007/s10514-015-9456-x
Autonomous Robots
Keywords
Field
DocType
Gaussian Process,Interest Point,Landing Site,Perception System,Trajectory Generation
Perception system,Computer vision,Optimal trajectory,Active perception,Simulation,Computer science,Vision based,Robustness (computer science),Artificial intelligence,Gaussian process,Perception,Trajectory
Journal
Volume
Issue
ISSN
39
3
0929-5593
Citations 
PageRank 
References 
4
0.45
33
Authors
7
Name
Order
Citations
PageRank
Vishnu R. Desaraju11069.01
Nathan Michael21892131.29
Martin Humenberger321715.74
Roland Brockers4779.62
Stephan Weiss5102258.90
Jeremy Nash6122.68
Larry H. Matthies795879.64