Kirill Khrustalev

Kharkiv National University of Radio Electronics

Papers

Total Citations

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About

Kirill Khrustalev is a researcher whose work sits at the intersection of computer vision and advanced manufacturing, with a particular focus on enhancing the intelligence and precision of robotic systems. His primary research areas include object recognition in aerial imagery using deep learning and the application of micro-electromechanical systems (MEMS) for adaptive process control in modular robotics. Khrustalev’s major contribution lies in improving object recognition models for aerial photographs captured by unmanned aerial vehicles, a critical challenge for computer vision systems. His 2021 paper on this topic, which has garnered 12 citations, details a refined convolutional neural network approach that enhances detection accuracy, directly supporting autonomous navigation and surveillance applications. In parallel, his 2018 work (9 citations) addresses a key manufacturing bottleneck by proposing the use of MEMS sensors to ensure ultrasonic wave orthogonality during the assembly of modular robots, thereby improving welding precision and process reliability. This dual focus—bridging perception and physical assembly—demonstrates a practical, systems-level approach to robotics. Khrustalev’s research is notable for its direct applicability to real-world automation challenges, offering tangible improvements in both how robots see and how they build.