Papers

4

Total Citations

35

H-Index

3

About

Takuro Sato is a researcher whose work spans robotics, sensor fusion, remote control systems, and radar-based sensing technologies. His foundational contribution came in 2002 with a widely recognized study on fusing vision and force sensor data to estimate contact positions between grasped objects and their environment — a technique critical for enabling robots to perform precise manipulation tasks. This work, which has accumulated 24 citations, established Sato as an early innovator in multi-modal robotic perception. Building on this foundation, Sato has more recently turned his attention to the challenges of remote robotic operation, particularly the problem of transmission latency in teleoperation systems. His 2023 work introduced a predictive compensation platform leveraging Long Short-Term Memory (LSTM) networks to bring effective latency to near-zero levels, earning 6 citations within a short period. A parallel 2024 study extended this approach to remote video monitoring systems using video prediction techniques. Additionally, Sato has contributed to radar-based sensing, exploring ultra-wideband (UWB) radar for multiple target tracking and separation in robotic and security contexts. Across his career, Sato's research consistently addresses the gap between theoretical robotics and real-world operational reliability.

Research Focus

Key Achievements

3
H-Index
4
Papers
35
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Estimation of contact position between a grasped object and the environment based on sensor fusion of vision and force
24 citations · 2002
📈 Most Prolific Year: 2002 (1 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: The University of Tokyo, Waseda University, Kyoto University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago