Papers
10
Total Citations
299
H-Index
6
About
Qijie Zhou is a robotics and control systems researcher whose career spans over three decades, with foundational contributions to robot manipulator control and more recent pioneering work in biologically inspired robotics. His early research in the 1990s established significant advances in variable structure and sliding mode control, most notably his adaptive variable structure model-following control (AVSMFC) framework for nonlinear robot trajectory tracking (116 citations) and a sliding mode algorithm for force/motion control of constrained robots (98 citations). These works addressed core challenges in robust control under uncertainty and remain influential references in the field. Zhou also explored neural network-based controllers and adaptive inverse dynamics schemes, demonstrating a consistent interest in bridging classical control theory with intelligent methods. In more recent years, his research has evolved toward deep reinforcement learning for manipulator control and bioinspired locomotion systems, exemplified by a locust-inspired robot capable of crawl–jump–gliding locomotion (19 citations), reflecting a compelling pivot toward embodied intelligence. With a citation profile exceeding 290 across diverse robotic domains, Zhou's work represents a sustained and evolving contribution to intelligent robotic systems research.
Research Focus
Key Achievements
Top Papers
- 1
- 2Force/motion control of constrained robots using sliding mode98 citations · 1992
- 3A Novel Variable Structure Control Scheme for Robot Trajectory Control26 citations · 1990
- 4Manipulator Control Method Based on Deep Reinforcement Learning20 citations · 2020
- 5
- 6
- 7Implicit adaptive inverse dynamics control of robot manipulators6 citations · 2002
- 8Adaptive sliding mode control of constrained robot manipulators3 citations · 2002
- 9
- 10A Robust Neural Network Controller2 citations · 1992