Papers
27
Total Citations
624
H-Index
14
About
Peidong Liang is a leading researcher in the field of physical human-robot interaction (pHRI), with a focus on enabling robots to learn and replicate human motor skills. His work centers on the transfer of human adaptive impedance to robotic systems, a critical advancement for creating robots that can interact safely and intuitively with people. Liang’s major contributions include pioneering methods to extract limb impedance from surface electromyography (sEMG) signals, allowing robots to mimic human stiffness and motion control. His most cited paper, “Interface Design of a Physical Human–Robot Interaction System for Human Impedance Adaptive Skill Transfer” (2017), has garnered 220 citations, underscoring its influence. He has also developed innovative teleoperation systems using Kinect sensors and MYO armbands to control robots like Baxter and Nao, enabling tasks such as handwriting and collaborative manipulation. Notably, his work on SVM-based classification of simultaneous hand movements from sEMG signals (32 citations) advances prosthetic control. Liang’s research, with over 500 total citations, bridges neuroscience, robotics, and rehabilitation, offering transformative solutions for human-robot collaboration in manufacturing, healthcare, and assistive technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2Teleoperation control of Baxter robot using body motion tracking38 citations · 2014
- 3
- 4SVM based simultaneous hand movements classification using sEMG signals32 citations · 2017
- 5
- 6An Augmented Discrete‐Time Approach for Human‐Robot Collaboration29 citations · 2016
- 7Teleoperated robot writing using EMG signals28 citations · 2015
- 8
- 9
- 10Development of Kinect based teleoperation of Nao robot20 citations · 2016