Sergey A. Chepinskiy
Papers
14
Total Citations
259
H-Index
8
About
Sergey A. Chepinskiy is a robotics researcher whose work spans soft robotics, mobile robot navigation, and intelligent control systems. He has made notable contributions to the emerging field of bio-inspired underwater soft robotics, most prominently through his groundbreaking work on bipedal walking underwater robots modeled after the coconut octopus, which has garnered 56 citations and represents a significant step toward environmentally harmonious underwater systems. His research extends to advanced control methodologies, including deep reinforcement learning for cable-driven soft arms and backstepping-based trajectory tracking for wheeled mobile robots, reflecting a sophisticated command of both classical and modern control theory. Chepinskiy has also made meaningful contributions to robot perception and navigation, developing hybrid CNN-SVM terrain classification methods and lightweight scene parsing networks that address the real-world constraints of onboard computation. His early work applying LEGO Mindstorms NXT platforms to teach adaptive control theory — with 36 citations — demonstrates a longstanding commitment to robotics education alongside research innovation. More recently, his development of a Human-Robot Empathy Decision-Making Model signals growing engagement with human-robot interaction for assistive applications. With papers accumulating hundreds of citations across over a decade of output, Chepinskiy's work bridges theoretical rigor and practical robotic deployment.
Research Focus
Key Achievements
Top Papers
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- 7Geometric path following control for an omnidirectional mobile robot11 citations · 2016
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