Runyi Yang
Papers
2
Total Citations
47
H-Index
2
About
Dr. Runyi Yang is a rising researcher at the intersection of 3D computer vision, robotics, and language-guided manipulation. Their work focuses on enabling robots to understand and interact with complex environments through natural language commands. Yang’s most notable contribution is **GaussianGrasper**, a pioneering system that constructs 3D language Gaussian splatting scenes for open-vocabulary robotic grasping. This work, which has already garnered 37 citations since 2024, allows robots to interpret human directives and manipulate objects without pre-defined categories—a critical step toward general-purpose service robots. Additionally, Yang has advanced large-scale robotic perception with their work on **city-scale continual neural semantic mapping**, which introduces three-layer sampling and panoptic representation to maintain up-to-date, detailed maps of dynamic urban environments (10 citations). This research bridges the gap between static mapping and real-world, ever-changing scenes. By combining language understanding with 3D spatial reasoning, Yang is pushing the boundaries of how robots perceive, learn, and act in human-centric spaces, making their work essential reading for anyone interested in embodied AI and autonomous manipulation.
Research Focus
Key Achievements
Top Papers
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- 2