Papers
14
Total Citations
273
H-Index
7
About
Dingkun Liang is a robotics and control systems researcher whose work centers on soft robotics, pneumatic artificial muscle (PAM) actuated systems, and intelligent control methodologies. His most significant contributions lie in developing advanced control frameworks for PAM-driven robots — biomimetic actuators that replicate human muscle behavior — addressing their inherent challenges such as nonlinearities, hysteresis, unidirectional input constraints, and dead zones. His 2021 paper on energy-based motion control for PAM-actuated robots has garnered 80 citations, while his fuzzy-sliding mode control approach for humanoid arm robots has attracted 66 citations, collectively establishing him as a prominent voice in compliant robot control for safe human-machine interaction. Beyond soft robotics, Liang has made meaningful contributions to underactuated systems, including self-balancing wheeled robots and wheeled inverted pendulums, employing techniques like differential flatness and trajectory planning. His more recent work has expanded into human-robot motion retargeting and point cloud-based place recognition, reflecting a broadening research agenda toward embodied intelligence. With a cumulative citation count exceeding 260, Liang's research offers both theoretical rigor and experimental validation, making his work particularly valuable for students and engineers working at the intersection of robot control, biomechanics-inspired actuation, and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5Modeling and motion control of self-balance robots on the slope12 citations · 2016
- 6
- 7Differential Flatness-Based Robust Control of Self-balanced Robots7 citations · 2018
- 8
- 9
- 10