Decision strategies for automated visual collision avoidance

Mcfadyen, Aaron, Durand-Petiteville, Adrien, & Mejias, Luis (2014) Decision strategies for automated visual collision avoidance. In Proceedings of the 2014 International Conference on Unmanned Aircraft Systems (ICUAS), IEEE, Orlando, Florida, The United States of America, pp. 715-725.

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Abstract

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

Impact and interest:

3 citations in Scopus
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1 citations in Web of Science®

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ID Code: 74392
Item Type: Conference Paper
Refereed: Yes
Keywords: Aircraft, Collision avoidance, Sprials, Trajectory, Vehicle dynamics, Vehicles, Visualization
DOI: 10.1109/ICUAS.2014.6842316
ISBN: 9781479923762
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 IEEE
Deposited On: 24 Jul 2014 23:05
Last Modified: 28 Jul 2014 00:10

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