Papers
14
Total Citations
172
H-Index
8
About
Daxiong Ji is a pioneering robotics researcher whose work spans the critical intersection of bio-inspired design, autonomous navigation, and multi-sensor integration for challenging environments. His research focuses on developing intelligent robotic systems for wall-climbing, underwater exploration, and multi-vehicle coordination. Ji’s most impactful contribution is the NeuroBayesSLAM framework (52 citations), which neurobiologically integrates Bayesian multisensory information for robot navigation, drawing inspiration from biological neural systems. He has also made significant advances in practical robotics, including the design of a permanent magnetic wheel-type adhesion-locomotion system for water-jetting wall-climbing robots (40 citations), enabling safer inspection of high structures. In underwater robotics, Ji developed an autonomous robotic fish for object detection and tracking (13 citations), and contributed to seafloor transponder calibration using improved perpendiculars intersection (9 citations). His work on visual detection and feature recognition of underwater targets using model-based methods (9 citations) addresses critical challenges in underwater imaging. Ji’s research has practical applications in autonomous inspection of steel box girders and tracking control of autonomous surface vehicles following underwater robots, demonstrating his commitment to solving real-world problems in hazardous environments.
Research Focus
Key Achievements
Top Papers
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- 8A tracking control method of ASV following AUV8 citations · 2013
- 9Multi-Beam Sonar Application on Autonomous Underwater Robot7 citations · 2015
- 10Underwater image matching by incorporating structural constraints6 citations · 2017