Zhendong Li
Papers
1
Total Citations
8
H-Index
1
About
Zhendong Li is a leading researcher in the field of robotic manipulation, with a primary focus on shared control, learning from demonstration, and contact-rich task execution. His most influential work introduces a learning-based shared control architecture for teleoperated contact tasks, where task models encoding desired motions, forces, and stiffness profiles are learned from human demonstrations. This learned information is then used to generate Virtual Fixtures (VFs) that guide operators, significantly improving precision and safety during physical interactions. With over 8 citations on this key 2023 publication, Li’s contributions are shaping how robots and humans collaborate in complex, force-sensitive environments. His research bridges the gap between autonomous learning and human-in-the-loop control, offering practical solutions for industrial assembly, surgical robotics, and remote maintenance. Li’s work stands out for its elegant integration of machine learning with real-time haptic feedback, making him a rising figure in the robotics community.
Research Focus
Key Achievements
Top Papers
- 1A Learning-Based Shared Control Approach for Contact Tasks8 citations · 2023