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Environments Diagnosis by Means of Computer Vision System of Autonomous Flying Robots

Environments Diagnosis by Means of Computer Vision System of Autonomous Flying Robots

Konstantin Dergachov, Anatolii Kulik, Anatolii Zymovin
Copyright: © 2019 |Pages: 23
ISBN13: 9781522577096|ISBN10: 1522577092|ISBN13 Softcover: 9781522585930|EISBN13: 9781522577102
DOI: 10.4018/978-1-5225-7709-6.ch004
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MLA

Dergachov, Konstantin, et al. "Environments Diagnosis by Means of Computer Vision System of Autonomous Flying Robots." Automated Systems in the Aviation and Aerospace Industries, edited by Tetiana Shmelova, et al., IGI Global, 2019, pp. 115-137. https://doi.org/10.4018/978-1-5225-7709-6.ch004

APA

Dergachov, K., Kulik, A., & Zymovin, A. (2019). Environments Diagnosis by Means of Computer Vision System of Autonomous Flying Robots. In T. Shmelova, Y. Sikirda, N. Rizun, D. Kucherov, & K. Dergachov (Eds.), Automated Systems in the Aviation and Aerospace Industries (pp. 115-137). IGI Global. https://doi.org/10.4018/978-1-5225-7709-6.ch004

Chicago

Dergachov, Konstantin, Anatolii Kulik, and Anatolii Zymovin. "Environments Diagnosis by Means of Computer Vision System of Autonomous Flying Robots." In Automated Systems in the Aviation and Aerospace Industries, edited by Tetiana Shmelova, et al., 115-137. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7709-6.ch004

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Abstract

In this chapter, the authors present an approach to the extrinsic environs diagnostics based on using visual information collected by autonomous robots. The possibility of utilizing a computer vision for the purpose of rational control implementation in the condition of the full or partial uncertainty is investigated. In the study, the combined hardware and software computer vision tools were verified. The models, algorithms, and codes for solving the local tasks of obstacle identification and mutual location kinematic parameters estimation have been developed. A series of computational and in-kind experiments that illustrate a practical possibility of implementing the navigational environment diagnosis is carried out with the aim to select a rational flight path.

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