Guofei Chen
Papers
2
Total Citations
3
H-Index
1
About
Guofei Chen is a rising researcher at the forefront of embodied AI and robotic perception, whose work bridges the gap between high-level language understanding and low-level physical interaction. His primary research areas include 3D scene understanding, spatial reasoning for robotics, and interactive path planning in cluttered environments. Chen’s major contributions are twofold: first, he developed SORT3D, a pioneering toolbox that leverages large language models for zero-shot 3D grounding, enabling robots to interpret complex, free-form natural language and accurately locate objects in three-dimensional space based on spatial relations and attributes. This work, already garnering early citations, promises to revolutionize human-robot collaboration. Second, his investigation into Search-Based Path Planning Among Movable Obstacles (PAMO) addresses a critical real-world challenge—allowing robots to intelligently push aside obstacles to find optimal, collision-free paths. By pursuing completeness in planning algorithms, Chen is laying the groundwork for robots that can autonomously navigate and manipulate dynamic, interactive environments, marking him as a key innovator in the next generation of autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2