Weiliang Ge

University of Electronic Science and Technology of China

Papers

Total Citations

312

H-Index

About

Weiliang Ge is a leading researcher in robotics and intelligent control systems, whose work has significantly advanced the modeling and adaptive control of humanoid and biped robots. His most influential contributions focus on addressing system uncertainties and complex dynamics in robotic locomotion and manipulation. Ge’s 2016 paper on model identification and control design for a humanoid robot (155 citations) established a foundational framework using the recursive Newton-Euler formula for upper-limb coordination. In parallel, his 2016 study on adaptive neural network control of biped robots (151 citations) pioneered the use of radial basis function neural networks to achieve robust balancing and posture control under uncertain conditions. These works have been widely cited for their practical solutions to real-world robotic challenges, such as handling output constraints and model inaccuracies. Ge’s research not only demonstrates high citation impact but also provides essential tools for engineers developing safer, more adaptive humanoid systems. His earlier work on approximation-based control with output constraints (2013) further underscores his sustained focus on constraint-aware, uncertainty-tolerant control design, making him a key figure in modern robotics and control theory.