Andrey V. Artemiev
Papers
1
Total Citations
5
H-Index
1
About
Andrey V. Artemiev is a researcher focused on the intersection of robotics, neural networks, and nonlinear system identification. His most cited work, "Robot dynamics identification via neural network" (2015), introduces a recurrent neural network (RNN)-based approach for modeling the complex, nonlinear dynamics of underwater robots (URs). Artemiev demonstrated that RNNs can be effectively trained to capture and predict a UR’s behavior, using data from a UR dynamics model to validate his approach. This contribution addresses a critical challenge in underwater robotics—accurate dynamic modeling for control and navigation—and has garnered 5 citations, reflecting its niche but growing influence. Beyond this paper, Artemiev’s research advances the use of machine learning for robotic system identification, offering practical pathways for improving autonomous underwater vehicle performance. His work is particularly valuable for students and researchers exploring neural network applications in robotics, nonlinear control, and marine engineering, providing a foundation for further innovations in adaptive and intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Robot dynamics identification via neural network5 citations · 2015