About

Stan Birchfield is a prominent computer vision and robotics researcher whose work spans robot navigation, object pose estimation, and dexterous robotic manipulation. With roots stretching back to foundational robotics work — including the celebrated DERVISH robot that won the 1994 AAAI Robot Competition (248 citations) — Birchfield has consistently advanced the frontier of intelligent, vision-driven robotic systems. His most impactful recent contributions center on deep learning for robotics. His 2018 paper on Deep Object Pose Estimation (DOPE), which addresses the challenging "reality gap" in synthetic training data for robotic grasping, has accumulated 283 citations and become a landmark reference in the field. He co-created DexYCB (250 citations), a widely adopted benchmark for hand-object grasping, and DexPilot (197 citations), a low-cost vision-based teleoperation system for dexterous robotic hands. Earlier contributions on qualitative vision-based robot navigation introduced elegant teach-and-replay approaches requiring only a single camera. His work on robotic laundry manipulation and hierarchical planning for long-horizon tasks further demonstrates the remarkable breadth of his research. Across more than two decades, Birchfield's research has profoundly shaped how robots perceive, plan, and interact with the physical world.

Research Focus

Key Achievements

19
H-Index
44
Papers
1,912
Total Citations
43
Avg Citations/Paper
🏆 Most Cited Paper
Deep Object Pose Estimation for Semantic Robotic Grasping of Household\n Objects
283 citations · 2018
📈 Most Prolific Year: 2021 (8 Papers)
🤝 Key Collaborators: 87
🏛 Institutions: Nvidia (United States), Clemson University, Aalto University, Nvidia (United Kingdom), Microsoft (United States), Georgia Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago