Chaoyi Xu
Papers
3
Total Citations
30
H-Index
3
About
Chaoyi Xu is a rising researcher in embodied AI and robot learning, whose work focuses on bridging perception, manipulation, and generalization in real-world robotic systems. His primary research areas include mobile manipulation, vision-language-guided object rearrangement, and scalable robot learning platforms. In his highly cited 2024 paper "GAMMA," Xu introduced a graspability-aware policy learning framework that fuses online grasping pose estimation with mobile base control, directly addressing the critical challenge of observing and grasping targets while approaching them—a fundamental bottleneck in mobile manipulation. This work has already garnered 20 citations for its practical impact on robotic assistants. Xu also contributed to "Open6DOR," a benchmark and VLM-based approach for open-instruction 6-DoF object rearrangement, pushing the boundaries of how large-scale vision-language models can be integrated with embodied agents to follow complex, open-ended commands. Additionally, his work on "RoboVerse" provides a unified platform, benchmark, and dataset aimed at scalable and generalizable robot learning. Through these contributions, Xu is helping to define the next generation of robots that can perceive, reason, and act in unstructured human environments.
Research Focus
Key Achievements
Top Papers
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