Papers
2
Total Citations
38
H-Index
2
About
Yurii Kulakov is a robotics researcher whose work focuses on autonomous navigation, perception, and multi-robot systems. His key contributions lie in developing robust solutions for dynamic and cluttered environments, with a particular emphasis on sensor fusion and collaborative mapping. His most cited work, "Efficient Obstacle Detection and Tracking Using RGB-D Sensor Data in Dynamic Environments for Robotic Applications" (2022, 24 citations), addresses the critical challenge of real-time obstacle detection for autonomous robots, leveraging RGB-D cameras to provide rapid environmental estimation. Building on this, Kulakov introduced CORB2I-SLAM (2022, 14 citations), an adaptive collaborative visual-inertial SLAM framework that enables multiple robots to generate robust global maps of unknown spaces. This work is notable for its flexibility in supporting monocular, stereo, or RGB-D cameras alongside inertial sensors, allowing each robot to contribute to a shared map. By tackling the complexities of dynamic environments and multi-agent coordination, Kulakov’s research advances the practical deployment of autonomous systems in real-world settings, making his work highly relevant for students and researchers in robotics, computer vision, and autonomous navigation.
Research Focus
Key Achievements
Top Papers
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