Chinkye Tan

Papers

Total Citations

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About

Chinkye Tan is a researcher in human-robot interaction (HRI), with a focused expertise in gesture recognition and collaborative robotics. Their most-cited work, "Gesture Recognition for Initiating Human-to-Robot Handovers" (2020, 8 citations), addresses a critical bottleneck in seamless human-robot collaboration: accurately detecting when a human intends to hand over an object. By framing this as a binary classification problem, Tan developed methods that enable robots to distinguish intentional handover gestures from incidental movements, preventing premature or unwanted object retrieval. This contribution is foundational for creating safer, more intuitive interactions in shared workspaces, particularly in manufacturing and assistive robotics. Tan’s research directly tackles the challenge of timing and intent in physical HRI, ensuring robots respond only when a human partner is ready. Their work has been cited in subsequent studies on predictive handover systems and social cue recognition, underscoring its influence on advancing autonomous robotic behavior. Through this focused line of inquiry, Chinkye Tan is helping to build the perceptual intelligence necessary for robots to become truly collaborative partners.