Computer Vision Based Collision Avoidance for UAVs

Carnie, Ryan J., Walker, Rodney A., & Corke, Peter I. (2005) Computer Vision Based Collision Avoidance for UAVs. In 11th Australian International Aerospace Congress, 14-17 March, 2005, Melbourne, Australia.


This research is investigating the feasibility of using computer vision to provide robust sensing capabilities suitable for the purpose of UAV collision avoidance. Presented in this paper is a preliminary strategy for detecting collision-course aircraft from image sequences and a discussion on its performance in processing a real-life data set.

Initial trials were conducted on image streams featuring real collision-course aircraft against a variety of daytime backgrounds. A morphological filtering approach was implemented and used to extract target features from background clutter. Detection performance in images with low signal to noise ratios was improved by averaging image features over multiple frames, using dynamic programming to account for target motion.

Preliminary analysis of the initial data set has yielded encouraging results, demonstrating the ability of the algorithm to detect targets even in situations where visibility to the human eye was poor.

Impact and interest:

Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

1,804 since deposited on 03 Jul 2006
101 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 4627
Item Type: Conference Paper
Refereed: No
Keywords: collision avoidance, UAV, computer vision, target detection
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2005 (please consult author)
Deposited On: 03 Jul 2006 00:00
Last Modified: 09 Jun 2010 12:33

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page