Fengxing Pan
Papers
1
Total Citations
6
H-Index
1
About
Fengxing Pan is a researcher at the forefront of embodied AI and autonomous systems, with a focus on integrating large multimodal models (LMMs) into physical robotics. His most cited work introduces a groundbreaking paradigm—"Agent as Cerebrum, Controller as Cerebellum"—which reimagines the architecture of industrial robotic agents. In this study, Pan demonstrates how LMMs can serve as the high-level reasoning "cerebrum" of a drone, while traditional controllers handle low-level motor tasks like the cerebellum. This approach, implemented in his AeroAgent framework, bridges the gap between cognitive AI and real-world drone operations, enabling more adaptive and intelligent autonomous flight. With 6 citations since 2023, this paper has quickly gained attention for its practical synthesis of AI and robotics. Pan’s contributions are particularly notable for their potential to transform industrial applications, from inspection to delivery, by making drones not just tools, but embodied agents capable of understanding and acting upon complex visual and linguistic commands. His work stands as a key step toward truly autonomous, context-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1