Benjamin Felbrich
Papers
4
Total Citations
128
H-Index
4
About
Benjamin Felbrich is a pioneering researcher at the intersection of computational design, robotic fabrication, and artificial intelligence. His work focuses on developing autonomous systems for architectural-scale additive manufacturing, particularly through the innovative use of deep reinforcement learning (DRL) and multi-robot collaboration. Felbrich’s most cited paper (50 citations) introduces a groundbreaking framework for autonomous robotic additive manufacturing using distributed model-free DRL, enabling robots to learn and adapt fabrication strategies in real-time within computational design environments. He is also renowned for his work on multi-machine fabrication, where he integrates autonomous unmanned aerial vehicles (UAVs) with industrial robots to construct long-span composite structures—a concept explored in multiple highly cited papers (32 and 25 citations). His research on physically distributed multi-robot coordination (25 citations) advances scalable construction methods, demonstrating how heterogeneous robot teams can collaborate on complex tasks. Felbrich’s contributions are notable for bridging the gap between theoretical AI and practical construction, pushing the boundaries of what is possible in automated building. His work has significant implications for reducing labor costs and enabling the fabrication of complex, lightweight architectural forms.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4