115 Copyright © 2019, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 4 DOI: 10.4018/978-1-5225-7709-6.ch004 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 in- vestigated. In the study, the combined hardware and software computer vision tools were verifed. The models, algorithms, and codes for solving the local tasks of obstacle identifcation and mutual location kinematic parameters estimation have been developed. A series of computational and in-kind experi- ments that illustrate a practical possibility of implementing the navigational environment diagnosis is carried out with the aim to select a rational fight path. BACKGROUND At present time, there is a trend of reducing the number of remotely piloted unmanned vehicles (UAVs) in sphere of aviation appliances. The more topical becomes the UAVs that are capable not only to fly autonomous fully but also perform monitoring, aerial photography, agricultural work, military missions, etc. Therefore, a UAV becomes an autonomous flying robot (AFR), which executes the basic functions without human being participation. Environments Diagnosis by Means of Computer Vision System of Autonomous Flying Robots Konstantin Dergachov National Aerospace University – Kharkiv Aviation Institute, Ukraine Anatolii Kulik National Aerospace University – Kharkiv Aviation Institute, Ukraine Anatolii Zymovin National Aerospace University – Kharkiv Aviation Institute, Ukraine