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Gaikwad, P and Mukhopadhyay, A and Muraleedharan, A and Mitra, M and Biswas, P (2023) DEVELOPING A COMPUTER VISION BASED SYSTEM FOR AUTONOMOUS TAXIING OF AIRCRAFT. In: Aviation, 27 (4). pp. 248-258.

AVI_27_4_2023.PDF - Published Version

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Official URL: https://doi.org/10.3846/aviation.2023.20588


Authors of this paper propose a computer vision based autonomous system for the taxiing of an aircraft in the real world. The system integrates both lane detection and collision detection and avoidance models. The lane detection component employs a segmentation model consisting of two parallel architec-tures. An airport dataset is proposed, and the collision detection model is evaluated with it to avoid collision with any ground vehicle. The lane detection model identifies the aircraft�s path and transmits control signals to the steer-control algorithm. The steer-control algorithm, in turn, utilizes a controller to guide the aircraft along the central line with 0.013 cm resolution. To determine the most effective controller, a comparative analysis is conducted, ultimately highlighting the Linear Quadratic Regulator (LQR) as the superior choice, boasting an average deviation of 0.26 cm from the central line. In parallel, the collision detection model is also compared with other state-of-the-art models on the same dataset and proved its superiority. A detailed study is conducted in different lighting conditions to prove the efficacy of the proposed system. It is observed that lane detection and collision avoidance modules achieve true positive rates of 92.59 and 85.19, respectively. © 2023 The Author(s). Published by Vilnius Gediminas Technical University.

Item Type: Journal Article
Publication: Aviation
Publisher: Vilnius Gediminas Technical University
Additional Information: The copyright for this article belongs to Author.
Keywords: Air navigation; Aircraft accidents; Aircraft control; Aircraft detection; Collision avoidance; Computer vision; Controllers; Object detection; Taxicabs, Airport dataset; Autonomous taxi; Collision detection; Collisions avoidance; Detection models; Lane detection; Lane navigation; Objects detection; Vision based; Vision-based system, Aircraft
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 01 Mar 2024 09:59
Last Modified: 01 Mar 2024 09:59
URI: https://eprints.iisc.ac.in/id/eprint/84029

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