Ivan Kholodilin
South Ural State University, Beijing Institute of Technology
Papers
3
Total Citations
17
H-Index
3
About
Ivan Kholodilin is a robotics researcher whose work focuses on digital-twin simulation, omnidirectional vision systems, and robotic calibration. His key contributions include developing a low-cost, cross-platform digital-twin simulation system for SCARA robots, which reduces algorithm testing costs and improves motion control fault tolerance—a practical solution for expensive physical robots. He has also advanced photorealistic simulators for omnidirectional vision systems, enabling efficient calibration and 3D reconstruction for mobile robot navigation, addressing the high cost of annotated training data in deep learning. Additionally, his work on calibrating omnidirectional vision systems for robotic sorting enhances distance measurement accuracy, critical for object manipulation tasks. With top-cited papers accumulating 7 and 5 citations respectively, Kholodilin’s research demonstrates tangible impact in bridging simulation and real-world robotics. His notable achievements include proposing modular communication frameworks and photorealistic environments that streamline algorithm development, making robotics more accessible and cost-effective. For students and researchers, Kholodilin’s work offers a blueprint for integrating simulation with vision-based robotics, emphasizing practical solutions to real-world challenges in automation and intelligent systems.
Research Focus
Key Achievements
Top Papers
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