Yusuke Tsuburaya
Papers
4
Total Citations
39
H-Index
3
About
Yusuke Tsuburaya is a robotics researcher advancing the frontier of human-robot interaction in crowded, dynamic environments. His primary research areas include crowd robot navigation, human motion prediction, and intent-conveyance systems for symbiotic mobile robots. Tsuburaya’s most significant contribution is the development of the **Inducible Social Force Model**, a novel framework that integrates reactive, proactive, and inducible behaviors to enable robots to navigate smoothly through human crowds. This work, published in 2022 and garnering 30 citations, addresses the critical challenge of robots getting stuck in dense pedestrian flows by allowing them to physically induce motion in humans through controlled forearm contact—a paradigm shift from purely avoidance-based strategies. His research also explores error-tolerant navigation, where robots sequentially convey their intent to humans to reduce hesitation and repetitive avoidance, as well as robust human velocity estimation using Kalman filters and least-squares methods with adjustable window sizes. Tsuburaya’s work is notable for its practical focus on real-world deployment, tackling the sensing and actuation limitations that plague current mobile robots. By prioritizing smooth, efficient movement over conservative safety stops, he is helping to create robots that can truly coexist with people in bustling spaces like airports, hospitals, and shopping centers.
Research Focus
Key Achievements
Top Papers
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