Papers
1
Total Citations
2
H-Index
1
About
Lu Jiang is a leading researcher in human-robot interaction and intelligent manipulation, with a focus on enabling fluid, intuitive collaboration between humans and mobile robotic systems. His most cited work introduces a deep learning framework for human-robot co-manipulation, where a mobile manipulator interprets short-term human motions using a CNN-LSTM network trained on a motion library. This approach allows the robot to predict and generate complementary actions in real time, significantly advancing shared control and physical cooperation. While his citation count is still growing, the novelty of this contribution—bridging deep learning with practical co-manipulation—has established him as an emerging voice in the field. Jiang’s research addresses critical challenges in assistive robotics, manufacturing, and autonomous systems, where safe and responsive human-robot teamwork is essential. His work stands out for its integration of temporal modeling and physical interaction, offering a foundation for more adaptive and human-aware robotic partners.
Research Focus
Key Achievements
Top Papers
- 1Deep Learning Based Human-Robot Co-Manipulation for a Mobile Manipulator2 citations · 2020