Tomohiro Maruyama

Papers

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About

Tomohiro Maruyama is a robotics researcher specializing in master-slave systems, teleoperation, and high-speed vision-based assist control. His work focuses on enhancing the maneuverability and dynamic performance of teleoperated robots, particularly in dangerous environments where human skillfulness must be replicated remotely. Maruyama’s most-cited paper (2017, 13 citations) introduces vision-based predictive assist control to improve reaching tasks in master-slave robots, effectively reproducing human-like dexterity and responsiveness. His 2016 paper (6 citations) further refines this approach by incorporating visual feedback and human intention into the control loop, enabling more intuitive and efficient operation. Another notable contribution (2016, 4 citations) applies high-speed vision to assist control for ball catching, demonstrating real-time dynamic performance in a lightweight master-slave system. Maruyama’s research bridges the gap between human skill and robotic precision, with potential applications in hazardous environments, surgery, and industrial automation. His work has garnered attention for its innovative integration of visual feedback and predictive algorithms, laying groundwork for more responsive and human-like teleoperation systems.