Aircraft collision avoidance using spherical visual predictive control and single point features

Mcfadyen, Aaron, Mejias, Luis, Corke, Peter, & Pradalier, Cedric (2013) Aircraft collision avoidance using spherical visual predictive control and single point features. In Amato, Nancy (Ed.) Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Tokyo Big Sight, Tokyo, pp. 50-46.

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Abstract

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

Impact and interest:

14 citations in Scopus
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10 citations in Web of Science®

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Full-text downloads:

170 since deposited on 28 Jul 2013
16 in the past twelve months

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ID Code: 61552
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: aircraft control, autonomous aerial vehicles, collision avoidance, control system synthesis, nonlinear control systems, optimisation, predictive control, robot vision
DOI: 10.1109/IROS.2013.6696331
ISSN: 2153-0858
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Copyright Statement: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
Deposited On: 28 Jul 2013 23:55
Last Modified: 26 Mar 2014 10:12

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