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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/18631

Title: Map-enhanced visual taxiway extraction for autonomous taxiing of UAVs
Authors: Lu, Bowen
Li, Baibing
Chen, Wen-Hua
Keywords: Knowledge-based systems
Taxiway centreline extraction
Issue Date: 2015
Publisher: Elsevier / © IFAC.
Citation: LU, B., LI, B. and CHEN, W.-H., 2015. Map-enhanced visual taxiway extraction for autonomous taxiing of UAVs. IFAC Papers online, 48(9), pp. 49–54.
Abstract: In this paper, a map-enhanced method is proposed for vision-based taxiway centreline extraction, which is a prerequisite of autonomous visual navigation systems for unmanned aerial vehicles. Comparing with other sensors, cameras are able to provide richer information. Consequently, vision based navigations have been intensively studied in the recent two decades and computer vision techniques are shown to be capable of dealing with various problems in applications. However, there are signi cant drawbacks associated with these computer vision techniques that the accuracy and robustness may not meet the required standard in some application scenarios. In this paper, a taxiway map is incorporated into the analysis as prior knowledge to improve on the vehicle localisation and vision based centreline extraction. We develop a map updating algorithm so that the traditional map is able to adapt to the dynamic environment via Bayesian learning. The developed method is illustrated using a simulation study.
Description: This paper was accepted for publication in the journal IFAC Papers online and the definitive published version is available at http://dx.doi.org/10.1016/j.ifacol.2015.08.058. It was presented at the 2015 IFAC Workshop on Advanced Control and Navigation for Autonomous Aerospace Vehicles, 10th-12th June 2015, Seville, Spain.
Sponsor: This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) Autonomous and Intelligent Systems programme under the grant number EP/J011525/1 with BAE Systems as the leading industrial partner.
Version: Accepted for publication
DOI: 10.1016/j.ifacol.2015.08.058
URI: https://dspace.lboro.ac.uk/2134/18631
Publisher Link: http://dx.doi.org/10.1016/j.ifacol.2015.08.058
ISSN: 1474-6670
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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