Papers
8
Total Citations
223
H-Index
7
About
Sergei Chernyi is a leading researcher in robotics and intelligent control systems, with a focus on autonomous navigation, soft robotics, and underwater vehicle technology. His work bridges deep learning, reinforcement learning, and fuzzy logic to solve complex real-world challenges. Chernyi pioneered a hybrid convolutional neural network and support vector machine method for visual terrain classification in mobile robots (50 citations), enabling efficient navigation under limited computational resources. He also advanced position control of cable-driven soft robotic arms using deep reinforcement learning (36 citations), addressing the unique difficulties of controlling deformable materials. In aerial robotics, he developed an intelligent autonomous navigation system for UAVs operating in randomly changing environments (31 citations). His contributions to underwater robotics are equally significant, including fuzzy motion control systems for autonomous underwater vehicles (24 citations) and foundational studies on underwater robotic systems (28 and 26 citations). Chernyi’s work on positioning and trajectory stabilization systems (21 citations) has applications spanning wearable, underwater, and space robotics. With over 200 total citations, his research is widely recognized for integrating data-driven modeling with robust control, pushing the boundaries of autonomous systems in unpredictable environments.
Research Focus
Key Achievements
Top Papers
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- 4The Use Robotics for Underwater Research Complex Objects28 citations · 2017
- 5Development of underwater robotics26 citations · 2017
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