Papers
2
Total Citations
50
H-Index
2
About
Mingyang Li is an emerging researcher working at the intersection of 3D scene understanding, computer vision, and multi-robot systems. His work spans two compelling domains: the integration of foundation models with advanced 3D representations, and cooperative intelligence for large-scale robotic systems. Li's most notable contribution, FMGS (Foundation Model Embedded 3D Gaussian Splatting), represents a significant step forward in holistic 3D scene understanding by embedding powerful foundation models directly into the 3D Gaussian Splatting framework. This work, which has garnered 42 citations since its 2024 publication, enables richer semantic comprehension of complex 3D environments — a capability with far-reaching implications for robotics, augmented reality, and autonomous systems. Beyond 3D vision, Li has also contributed to the field of multi-robot coordination, proposing a novel cooperative path planning method leveraging UCR-FCE and behavior regulation techniques to address the challenges of orchestrating large-scale robot swarms. Though a younger contribution with 8 citations, it demonstrates his broader ambition to bridge perception and action in intelligent systems. Li's research reflects a forward-thinking approach to building machines that can both understand and navigate the physical world.
Research Focus
Key Achievements
Top Papers
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