Papers
9
Total Citations
189
H-Index
7
About
Yitao Ding is a leading researcher in safe human-robot interaction, specializing in capacitive tactile proximity sensing and collision avoidance for robotic manipulators. His work bridges the gap between perception and safety, enabling robots to detect and react to nearby objects and humans without physical contact. Ding’s major contributions include developing proximity sensor skins that measure distance and material properties, and introducing “proximity servoing” for real-time collision avoidance in redundant serial robots. His most-cited paper (2013, 47 citations) demonstrates safe interaction using capacitive sensor arrays, while his 2020 work (39 citations) advances on-line collision avoidance with low-latency perception. He has also pioneered contactless material detection using impedance spectroscopy and machine learning (2018, 25 citations; 2020, 13 citations), enhancing robotic grasping and adaptation. His 2021 study (16 citations) improves impedance-controlled manipulators’ safety and accuracy through proactive impact reactions. Ding’s research has been recognized for its practical impact on human-robot collaboration, with a unified benchmark (2021, 11 citations) standardizing capacitive proximity sensing evaluation. His work continues to shape safer, more intuitive robotic systems for industrial and collaborative environments.
Research Focus
Key Achievements
Top Papers
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- 3With Proximity Servoing towards Safe Human-Robot-Interaction30 citations · 2019
- 4Capacitive Proximity Sensor Skin for Contactless Material Detection25 citations · 2018
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