Vision-based pose estimation of a multi-rotor unmanned aerial vehicle
International Journal of Intelligent Unmanned Systems
ISSN: 2049-6427
Article publication date: 2 April 2019
Issue publication date: 13 June 2019
Abstract
Purpose
The purpose of this paper is to facilitate autonomous landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving/tilting platform using a robust vision-based approach.
Design/methodology/approach
Autonomous landing of a multi-rotor UAV on a moving or tilting platform of unknown orientation in a GPS-denied and vision-compromised environment presents a challenge to common autopilot systems. The paper proposes a robust visual data processing system based on targets’ Oriented FAST and Rotated BRIEF features to estimate the UAV’s three-dimensional pose in real time.
Findings
The system is able to visually locate and identify the unique landing platform based on a cooperative marker with an error rate of 1° or less for all roll, pitch and yaw angles.
Practical implications
The proposed vision-based system aims at on-board use and increased reliability without a significant change to the computational load of the UAV.
Originality/value
The simplicity of the training procedure gives the process the flexibility needed to use a marker of any unknown/irregular shape or dimension. The process can be easily tweaked to respond to different cooperative markers. The on-board computationally inexpensive process can be added to off-the-shelf autopilots.
Keywords
Acknowledgements
This research is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) under the Discovery Grant program, and MITACS under the Globalink and Graduate Fellowship program.
Citation
Gupta, K., Emran, B.J. and Najjaran, H. (2019), "Vision-based pose estimation of a multi-rotor unmanned aerial vehicle", International Journal of Intelligent Unmanned Systems, Vol. 7 No. 3, pp. 120-132. https://doi.org/10.1108/IJIUS-10-2018-0030
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited