Kazuhiko Tamesue
Papers
2
Total Citations
9
H-Index
2
About
Kazuhiko Tamesue is a researcher at the forefront of human-robot interaction and remote systems engineering, with a specialized focus on tackling one of the most persistent challenges in teleoperation: communication latency. His work addresses the fundamental limitations that arise when controlling robotic systems and monitoring environments across networks, where transmission delays can critically impair efficiency and usability. Tamesue's most notable contribution lies in his innovative application of Long Short-Term Memory (LSTM) neural networks to predictively compensate for transmission delays in remote robot control, effectively reducing perceived latency to near-zero levels — a breakthrough that has earned his 2023 study 6 citations within a short period. Building on this foundation, his 2024 research extends the predictive compensation approach to video monitoring systems, acknowledging the theoretical impossibility of true zero-latency while engineering practical solutions that bring performance remarkably close to that ideal, garnering 3 citations since publication. Taken together, Tamesue's research represents a meaningful step forward in making teleoperation and remote monitoring more responsive and reliable — work with broad implications for fields ranging from industrial robotics and remote surgery to disaster response and autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2