Takashi Okuda

Papers

Total Citations

H-Index

About

Takashi Okuda’s research lies at the intersection of robotics, network engineering, and artificial intelligence, with a particular focus on Quality of Service (QoS) control for remote robot systems. His most cited work investigates how network delays and cloud computing affect force feedback in teleoperated robots—a critical challenge for applications requiring precise, real-time haptic interaction. By integrating neural network models into QoS control, Okuda has developed methods to improve robot position accuracy and responsiveness under variable network conditions, directly addressing the latency and reliability issues that plague remote robotic systems. His 2020 paper on the influence of network delay on QoS control using neural networks has garnered 8 citations, while his 2021 follow-up exploring neural network-driven position control using force information has received 4 citations. Beyond these technical contributions, Okuda’s earlier work (2006) offers a unique perspective on humanoid robots as social communication media, proposing a new metrology for usability testing that considers social interaction in home and office environments. This broader view—bridging hard engineering problems with human-robot interaction—distinguishes his research and underscores its relevance as robots become increasingly integrated into everyday life.