Papers
1
Total Citations
23
H-Index
1
About
Haolong Li is a robotics researcher specializing in state estimation, autonomous navigation, and sensor fusion for mobile robotic systems. His work sits at the intersection of computer vision, inertial sensing, and motion modeling — a domain critical to enabling robots to navigate reliably in real-world environments under practical constraints such as limited power and payload capacity. Li's most notable contribution to date is his development of a novel Visual-Inertial Odometry (VIO) framework that integrates online calibration of velocity-control based kinematic motion models for wheeled mobile robots. Published in 2022, this work advances the field by combining stereo camera data with inertial measurements while simultaneously calibrating the robot's kinematic model in real time — a significant step toward more adaptive and robust autonomous systems. This paper has already garnered 23 citations, reflecting meaningful early impact within the robotics and autonomous systems community. His research addresses a fundamental challenge in robotics: achieving accurate, low-cost localization without relying on GPS or heavyweight sensing infrastructure. By making VIO systems smarter and more self-calibrating, Li's contributions hold direct implications for applications ranging from warehouse automation to field robotics, positioning him as a promising voice in the next generation of autonomous navigation research.
Research Focus
Key Achievements
Top Papers
- 1