Papers
4
Total Citations
149
H-Index
4
About
Dr. Kaiyuan Gao is a leading researcher at the intersection of advanced manufacturing and multi-robot systems, making significant contributions to both robotic precision machining and cooperative localization. His primary research areas include intelligent robotic belt grinding of superalloys and multi-robot cooperative positioning using ultra-wideband (UWB) sensors. Dr. Gao’s most impactful work, a novel material removal prediction method for robotic belt grinding of Inconel 718 using acoustic sensing and an ensemble XGBoost learning algorithm, has garnered 85 citations and represents a major advance in precision manufacturing for difficult-to-machine materials. He has also published a comprehensive review on recent advances in robotic belt grinding of superalloys (29 citations). In the field of multi-robot systems, Dr. Gao proposed a cooperative localization system using UWB sensors and GPU acceleration to mitigate non-line-of-sight errors in complex indoor environments (26 citations), and developed a Bayesian filtering approach for error mitigation in UWB ranging (9 citations). His work bridges critical gaps between intelligent sensing, real-time computation, and manufacturing automation, establishing him as a key innovator in both industrial robotics and autonomous multi-agent systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2A review of recent advances in robotic belt grinding of superalloys29 citations · 2023
- 3
- 4