Nicholas Brian DePalma
Papers
1
Total Citations
2
H-Index
1
About
Nicholas Brian DePalma is a researcher at the intersection of human-robot interaction, gesture generation, and multimodal communication. His work focuses on how robots can use co-speech gestures to improve the clarity and naturalness of instructions, particularly in ambiguous or complex scenarios. DePalma’s major contribution is a data-driven framework that captures human gestures via motion capture, retargets them to robots, and selects optimal gestures, arm configurations, and standing formations to maximize understandability. This approach, detailed in his most-cited paper "Toward a One-interaction Data-driven Guide: Putting Co-speech Gesture Evidence to Work for Ambiguous Route Instructions" (2021, 2 citations), represents a pioneering step toward one-shot, interaction-efficient robotic guidance. While his citation count is still growing, DePalma’s work is notable for bridging empirical gesture studies with practical robotics, offering a pipeline that reduces the need for multiple interactions. His research holds promise for applications in assistive robotics, navigation aids, and human-robot teamwork, making him a rising voice in the effort to make robot communication more intuitive and human-like.
Research Focus
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Top Papers
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