Shumpei Hatanaka
Papers
1
Total Citations
2
H-Index
1
About
Shumpei Hatanaka is a researcher advancing the field of domestic service robotics (DSRs) with a focus on linguistic explainability and proactive risk prediction. His work bridges computer vision, natural language generation, and human-robot interaction, aiming to make robots not only functional but also transparent in their decision-making. His most-cited paper, "Nearest neighbor future captioning: generating descriptions for possible collisions in object placement tasks" (2024, 2 citations), introduces a novel method for robots to anticipate and verbally describe potential accidents—such as collisions—before they occur. This contribution addresses a critical gap in DSRs: the inability to communicate future risks from their own actions. By leveraging nearest-neighbor retrieval and captioning techniques, Hatanaka enables robots to generate context-aware, human-readable warnings, enhancing safety and trust in autonomous systems. His work is particularly notable for its practical application in object placement tasks, where precise spatial reasoning is essential. Though early in his career, Hatanaka’s research has already garnered attention for its innovative integration of explainability into robotic planning, offering a pathway toward more intuitive and accountable domestic robots. His efforts underscore a commitment to making AI systems not just capable, but also comprehensible to everyday users.
Research Focus
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Top Papers
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