A. Belyaev

National Research Tomsk State University

Papers

Total Citations

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About

A. Belyaev is a researcher in mobile robotics and artificial intelligence, with a primary focus on navigation systems for autonomous robots operating in complex, heterogeneous environments. Their major contribution lies in pioneering the application of inductive modeling, specifically the Group Method of Data Handling (GMDH), to create learning-based navigation systems for mobile robots. Belyaev’s work addresses the critical challenge of outdoor robots functioning in a priori unknown environments, introducing a novel approach that enables robots to adapt and learn navigation strategies in real time. Their key papers, including "Navigation learning system for mobile robot in heterogeneous environment: Inductive modeling approach" and "GMDH-Based Learning System for Mobile Robot Navigation in Heterogeneous Environment," each with 3 citations, represent foundational steps in merging inductive modeling with robotics. Though early in citation impact, Belyaev’s research is notable for its innovative integration of machine learning techniques into practical robotic navigation, offering a fresh perspective on autonomous decision-making. This work holds promise for advancing adaptive robotics in unstructured settings, making it a valuable reference for students and researchers exploring intelligent navigation systems.