Papers
33
Total Citations
832
H-Index
17
About
Qing Gao is a prominent researcher whose work bridges robotics, computer vision, and human-robot interaction (HRI), with particular expertise in hand gesture recognition, space robotics, and intelligent robot control. His most cited contribution, "Dynamic Hand Gesture Recognition Based on 3D Hand Pose Estimation for Human–Robot Interaction" (2021, 115 citations), exemplifies his commitment to developing intuitive interfaces between humans and robotic systems. Gao has made significant strides in dexterous robot teleoperation, advancing bimanual motion capture and RGB-D gesture detection frameworks that enable natural, flexible robotic manipulation. His work extends into life-critical applications, notably designing a 9-DOF rigid-flexible robot for COVID-19 swab sampling to protect healthcare workers. Beyond HRI, Gao has contributed to depth completion for autonomous systems (70 citations), space robotics control using fuzzy sliding mode algorithms, and multi-arm robot decoupling using time-delay estimation (75 citations). His 2023 research on skeleton-based action recognition and dual-hand motion capture reflects his continued innovation in human-centered robotics. With over 580 cumulative citations across his leading works, Gao's research meaningfully advances safe, intelligent, and responsive human-robot collaboration across industrial, medical, and space domains.
Research Focus
Key Achievements
Top Papers
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- 3Deep Depth Completion from Extremely Sparse Data: A Survey70 citations · 2022
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