Lipeng Chen
Papers
20
Total Citations
312
H-Index
11
About
Lipeng Chen is a leading researcher at the intersection of robotics, human-robot interaction, and tactile sensing. Their work focuses on making physical human-robot collaboration (pHRC) safer, more intuitive, and more comfortable. Chen’s key contributions include developing novel frameworks for human comfortability during manipulation, introducing muscular-informed metrics and peripersonal-space planning to optimize collaborative tasks. They have also pioneered advancements in visuotactile sensing, notably through the GelStereo Palm—a curved sensor for 3-D geometry sensing—and self-supervised contact geometry learning, enabling robots to perceive touch with unprecedented fidelity. With over 250 citations across their top ten papers, Chen’s impact is evident. Their work on shear-thickening fluid controllers for compliant yet resistive pHRI and vision-based intention inference during human-robot interaction has opened new avenues for safe, adaptive robotics. Additionally, Chen’s research extends to assistive technologies, including intelligent walking support robots for sit-to-stand transitions and egocentric trajectory forecasting for visually impaired individuals. Their interdisciplinary approach—merging ergonomics, biomechanics, and deep learning—positions them as a pivotal figure shaping the future of collaborative and assistive robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Self-Supervised Contact Geometry Learning by GelStereo Visuotactile Sensing32 citations · 2021
- 3
- 4
- 5GelStereo Palm: A Novel Curved Visuotactile Sensor for 3-D Geometry Sensing25 citations · 2023
- 6
- 7
- 8Design of End-effector for Kiwifruit Harvesting Robot Experiment20 citations · 2017
- 9
- 10Manipulation Planning Under Changing External Forces16 citations · 2018