Yuto Nagai

Papers

Total Citations

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About

Yuto Nagai is a robotics researcher whose work centers on autonomous navigation and human detection for service robots. His most cited paper, "A Method for Detecting Human by 2D-LiDAR" (2022, 8 citations), addresses a critical challenge in developing safe, socially aware robotic carts for transport, guidance, delivery, and patrol. Nagai’s key contribution lies in using 2D-LiDAR—a cost-effective and widely available sensor—to distinguish humans from other obstacles, enabling robots to detect vulnerable individuals like elderly wanderers without relying on expensive or privacy-intrusive cameras. This work directly supports the creation of patrol robots that can identify and assist people in need while navigating autonomously via localization and mapping. Though early in his career, Nagai’s focus on practical, low-cost sensing for human-robot interaction has immediate applications in healthcare and public safety. His research bridges the gap between robust autonomous mobility and nuanced human perception, promising safer coexistence with robots in shared spaces. As autonomous service robots become more common, Nagai’s methods offer a scalable path to making them both aware and considerate of the people around them.