Alexander Demin

Siberian Branch of the Russian Academy of Sciences, Sobolev Institute of Mathematics

Papers

Total Citations

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About

Alexander Demin is a researcher focused on advancing adaptive control systems for modular and multiped robots. His work centers on developing intelligent, self-learning control architectures that enable robots with arbitrary, reconfigurable designs to autonomously solve locomotion problems. Demin’s major contributions include the introduction of a logical-probabilistic method for adaptive control, which leverages functional similarity among modules and a directed search algorithm for rule discovery. This approach allows for joint training of control modules, starting from common rules and progressively refining them. His most cited papers—"Adaptive Control of Modular Robots" (2017, 4 citations) and "Adaptive control of multiped robot" (2018, 4 citations)—lay the groundwork for this methodology, while his 2020 work on "Adaptive locomotion control system for robots with arbitrarily modular design" (2 citations) extends the framework to hyper-redundant systems. Demin’s research is notable for its emphasis on knowledge discovery and pattern learning, offering a scalable solution for robots with varying morphologies. Though his citation counts are modest, his work represents a foundational step toward truly adaptive, modular robotics.