Papers
7
Total Citations
44
H-Index
4
About
Zhigu Liu is a leading researcher in advanced robotics control, specializing in adaptive and disturbance-rejection methods for humanoid, quadruped, and underwater robotic systems. His most impactful work introduces a sliding mode nonlinear disturbance observer-based adaptive back-stepping controller for humanoid dual manipulators (12 citations), enabling robust attitude control under system uncertainty. He further advanced this field with a fuzzy-approximation adaptive backstepping approach for coordinated dual-arm trajectory tracking (11 citations), bringing humanoid robots closer to human-like object manipulation. Liu has also made significant contributions to state estimation for quadruped robots navigating non-stationary terrain, combining invariant extended Kalman filters with disturbance observers (4 citations) to enhance stability in demanding environments like rescue and agriculture. His work extends to over-actuated underwater vehicles, where he applies active disturbance rejection control and optimal thrust allocation for auto-heading under water currents (2 citations). Additionally, Liu has developed 3D perception algorithms using RGB-enhanced point cloud fusion (9 citations) for random environment sensing. With over 40 total citations across his portfolio, Liu’s research consistently bridges theoretical control innovation with practical robotic autonomy, making him a key figure in the evolution of resilient, perceptive robotic systems.
Research Focus
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