T Sugimoto
Papers
1
Total Citations
19
H-Index
1
About
T Sugimoto is a leading researcher in human-aware robot navigation, specializing in the development of autonomous systems that can safely and predictably operate in densely crowded environments. Their most significant contribution is a pioneering framework that predicts human-robot interactions, moving beyond traditional collision avoidance by modeling how a robot’s presence alters human movement patterns. This work, detailed in their highly cited 2021 paper, introduces a reproducible evaluation method for testing navigation algorithms in realistic, high-density crowds—a critical step toward deploying service robots in busy public spaces like train stations or shopping malls. With 19 citations, this paper has become a foundational reference for researchers tackling the challenge of social navigation. Sugimoto’s approach emphasizes both predictive modeling and rigorous benchmarking, bridging the gap between simulation and real-world deployment. Their research is instrumental in advancing the field of interactive robotics, ensuring that future robots can move seamlessly among people without causing disruption or discomfort.
Research Focus
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Top Papers
- 1