Papers
11
Total Citations
38
H-Index
3
About
Ryhor Prakapovich is a robotics researcher whose work spans the core challenges of making robots move intelligently and efficiently. His research focuses on the kinematics, dynamics, and control of both anthropomorphic and mobile robotic systems. A key contribution is his iterative method for solving the inverse kinematics problem for multi-link robots with rotational joints, a fundamental challenge in robotics. Prakapovich has also made significant strides in control system optimization, employing genetic algorithms to tune PID controllers for line-following robots and leveraging reinforcement learning for automatic motion control. His work on the stability of the anthropomorphic robot Antares under external loads, which has garnered 9 citations, demonstrates his commitment to practical, structural analysis. Further notable achievements include developing imitation learning methods for neural network-based maze navigation and exploring energy-efficient motion through multiple analytical solutions for inverse kinematics. With a portfolio of papers addressing human-robot interaction, distributed systems for collaborative robots, and forced motion control, Prakapovich is contributing to the foundational software and control logic that will enable more autonomous, efficient, and capable robots.
Research Focus
Key Achievements
Top Papers
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- 5Forced motion control of a mobile robot3 citations · 2022
- 6Language Modeling for Robots-Human Interaction3 citations · 2016
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- 9Distributed Information System for Collaborative Robots and IoT Devices2 citations · 2016
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