Papers
5
Total Citations
59
H-Index
4
About
Jianqi Liu is a researcher whose work sits at the intersection of robotics, computer vision, and intelligent systems, with particular expertise in visual tracking, simultaneous localization and mapping (SLAM), and robotic control. His most cited contribution, "LiteTrack" (2024, 25 citations), demonstrates a keen ability to bridge cutting-edge transformer-based vision models with the practical demands of real-time robotics, introducing layer pruning and asynchronous feature extraction to deliver lightweight yet high-performing visual trackers suitable for edge deployment. His work on adaptive prescribed settling time control for robotic manipulators (2023, 17 citations) reflects a strong foundation in control theory, addressing the challenge of reliable robot operation under uncertainty and state constraints. Earlier research on deep learning-based relocalization for SLAM (2017, 10 citations) highlights his long-standing interest in robust robot navigation. More recent contributions, including dynamic parameter identification using radial basis function neural networks and the lifelong localization system LL-Localizer, underscore his commitment to building robots that remain accurate and adaptable in complex, changing environments. Across his career, Liu's research consistently pushes toward smarter, more deployable robotic intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5LL-Localizer: A Lifelong Localization System Based on Dynamic i-Octree3 citations · 2025