Kenta Tohashi

University of Aizu, Fuji Machine (Japan)

Papers

Total Citations

H-Index

About

Kenta Tohashi is a researcher at the forefront of robotics and industrial automation, with a focus on teleoperation systems and deep learning applications for plant inspection. His work addresses critical challenges in remote manipulation and infrastructure monitoring, blending virtual reality with robotic control to enhance operator efficiency and safety. Tohashi’s most-cited paper, “Dual-arm robot teleoperation support with the virtual world” (2020, 9 citations), introduces a novel framework that integrates a virtual environment to improve the precision and intuitiveness of dual-arm robot control, enabling more complex tasks in hazardous or inaccessible settings. Complementing this, his study “Automatic analog meter reading for plant inspection using a deep neural network” (2020, 5 citations) demonstrates a practical deep learning solution for automating the reading of analog gauges—a common yet tedious task in industrial maintenance—achieving robust performance in real-world conditions. Though his citation counts are modest, Tohashi’s contributions are notable for their direct applicability to industry, bridging the gap between advanced research and operational needs. His work exemplifies how virtual reality and AI can revolutionize traditional inspection and teleoperation processes, making him a promising voice in the evolution of smart manufacturing and remote robotics.