Fengjunjie Pan

Technical University of Munich, Fraunhofer Institute for Manufacturing Engineering and Automation

Papers

Total Citations

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About

Fengjunjie Pan is a robotics researcher advancing the frontiers of cloud-native fog robotics, intelligent force control, and anomaly detection for industrial automation. His work addresses critical challenges in deploying real-time robotic applications by integrating fog computing and cloud-native architectures, enabling enhanced flexibility and computational power without sacrificing performance—a contribution that is foundational for next-generation, multi-functional robotic systems. Pan has also pioneered a transferable force controller based on prescribed performance, solving the persistent industry problem of re-tuning controller parameters when tasks are moved between different robots, thereby streamlining contact establishment in robotic assembly. Additionally, he has developed a knowledge-augmented anomaly detection method using Transformer-based reconstruction networks to identify irregularities in semantic temporal process data, specifically tailored for small-lot production environments. Though early in his career, his research has already garnered citations in top venues, reflecting its growing impact. Pan’s work sits at the intersection of real-time systems, cloud robotics, and industrial AI, offering practical solutions that bridge theory and application. His innovative approaches are poised to shape the future of flexible, intelligent, and resilient robotic automation.