Zhiqi Li
Papers
16
Total Citations
271
H-Index
7
About
Zhiqi Li is a leading researcher in intelligent robotic manipulation, with a focus on autonomous grasping, space robotics, and real-time control systems. His most influential work, "Robot grasp detection using multimodal deep convolutional neural networks" (158 citations), pioneered the use of deep learning to enable robots to perceive and grasp objects in unstructured environments, addressing a critical bottleneck in autonomous manipulation. Li has made significant contributions to space robotics, including the development of a robotic hand-arm system for on-orbit servicing missions aboard China’s Tiangong-2 Space Laboratory, and the design of a modular space telescope assembly system—both of which demonstrate his work’s real-world impact in extreme environments. His research also advances industrial robotics through gravity compensation algorithms and real-time control frameworks using ROS and EtherCAT, improving robot safety and precision. With over 250 total citations, Li’s work bridges deep learning, sensor fusion, and control theory, offering practical solutions for both terrestrial and space applications. His achievements highlight a career dedicated to making robots more capable, adaptive, and deployable in complex, real-world scenarios.
Research Focus
Key Achievements
Top Papers
- 1Robot grasp detection using multimodal deep convolutional neural networks158 citations · 2016
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- 6Research on Gravity Compensation of Robot Arm Based on Model Learning8 citations · 2019
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- 9Design of a Ring-Type Bearingless Torque Sensor With Low Crosstalk Error6 citations · 2022
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