Zhuqing Jiang
Papers
3
Total Citations
59
H-Index
3
About
Zhuqing Jiang is a leading researcher in robotics perception and autonomous navigation, with a core focus on multi-sensor fusion for state estimation and simultaneous localization and mapping (SLAM). His most significant contribution is the development of Lvio-Fusion, a self-adaptive, tightly coupled SLAM framework that intelligently fuses data from stereo cameras, IMUs, and other sensors. By integrating an actor-critic reinforcement learning method, this framework dynamically adjusts sensor weighting based on environmental conditions—a critical advancement for mobile robots operating in varied and unpredictable settings. This work has garnered over 50 citations, underscoring its impact on the field. Jiang has also explored novel approaches to video prediction, using Taylor representation to disentangle temporal dynamics for more accurate forecasting. His research directly addresses the fundamental challenge of robust state estimation, enabling robots to navigate reliably in complex environments. Through his innovative fusion techniques and adaptive algorithms, Jiang is shaping the next generation of autonomous systems, making his work essential reading for students and engineers advancing mobile robotics and intelligent perception.
Research Focus
Key Achievements
Top Papers
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