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Open AccessArticle

Single-Camera Trilateration

by 1,*, 2, 2 and 2
Department of Engineering, College of Engineering, State University of New York Polytechnic Institute, Utica, NY 13502, USA
Department of Mechanical Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794, USA
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(24), 5374;
Received: 2 October 2019 / Revised: 27 November 2019 / Accepted: 4 December 2019 / Published: 9 December 2019
(This article belongs to the Special Issue Recent Advances in Indoor Localization Systems and Technologies)
This paper presents a single-camera trilateration scheme which estimates the instantaneous 3D pose of a regular forward-looking camera from a single image of landmarks at known positions. Derived on the basis of the classical pinhole camera model and principles of perspective geometry, the proposed algorithm estimates the camera position and orientation successively. It provides a convenient self-localization tool for mobile robots and vehicles equipped with onboard cameras. Performance analysis has been conducted through extensive simulations with representative examples, which provides an insight into how the input errors and the geometric arrangement of the camera and landmarks affect the performance of the proposed algorithm. The effectiveness of the proposed algorithm has been further verified through an experiment. View Full-Text
Keywords: localization; trilateration; mobile robots localization; trilateration; mobile robots
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MDPI and ACS Style

Zhou, Y.; Liu, W.; Lu, X.; Zhong, X. Single-Camera Trilateration. Appl. Sci. 2019, 9, 5374.

AMA Style

Zhou Y, Liu W, Lu X, Zhong X. Single-Camera Trilateration. Applied Sciences. 2019; 9(24):5374.

Chicago/Turabian Style

Zhou, Yu; Liu, Wenfei; Lu, Xionghui; Zhong, Xu. 2019. "Single-Camera Trilateration" Appl. Sci. 9, no. 24: 5374.

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