Snapshot-based control of UAS hover in outdoor environments

Denuelle, Aymeric, Strydom, Reuben and Srinivasan, Mandyam V. (2015). Snapshot-based control of UAS hover in outdoor environments. In: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE International Conference on Robotics and Biomimetics, Zuhai, China, (1278-1284). 6-9 December 2015. doi:10.1109/ROBIO.2015.7418947


Author Denuelle, Aymeric
Strydom, Reuben
Srinivasan, Mandyam V.
Title of paper Snapshot-based control of UAS hover in outdoor environments
Conference name IEEE International Conference on Robotics and Biomimetics
Conference location Zuhai, China
Conference dates 6-9 December 2015
Convener IEEE
Proceedings title 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)
Journal name 2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015
Place of Publication Piscataway, NJ, United States
Publisher IEEE (Institute for Electrical and Electronic Engineers)
Publication Year 2015
Sub-type Fully published paper
DOI 10.1109/ROBIO.2015.7418947
ISBN 9781467396752
Start page 1278
End page 1284
Total pages 7
Collection year 2016
Language eng
Abstract/Summary With the emergence of rotorcraft unmanned aerial systems (UAS) in civilian applications, the capability of accurate visual hovering is required in near-ground, GPS-denied, flying operations. Optic flow is commonly used for vision-based guidance and control of UAS, enabling autonomous obstacle avoidance, speed regulation, odometry, etc. This paper presents an optic flow-based method that uses a bio-inspired concept of image matching for the control of drift-free hover in natural environments. Our approach uses a reference snapshot (panoramic image) taken at the desired hover location and, through optic flow measurements, it estimates the rotorcraft's 3D position and velocity relative to that location by matching the current and reference views at each time step. These position and velocity signals are fed to a hover controller. Sensing and control are performed in real-time, at camera frame rate (25Hz) onboard a small-size, custom-built quadrotor, and without additional sensor fusion. Results from outdoor closed-loop flight tests demonstrate robustness against long-term drift, as well as improved hover accuracy when compared to techniques that use frame-to-frame integration of egomotion vectors derived from optic flow.
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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