Eudald Romo

Massachusetts Institute of Technology

Papers

3

Total Citations

706

H-Index

3

About

Eudald Romo is a leading researcher in robotic manipulation, with a core focus on enabling robots to reliably grasp and recognize objects in unstructured, cluttered environments. His most influential work centers on developing a novel pick-and-place system that combines multi-affordance grasping with cross-domain image matching. This breakthrough allows robots to handle a wide range of object categories—both known and entirely novel—without requiring any task-specific training data for the new items. The flagship paper on this system has amassed over 460 citations, reflecting its profound impact on the field of robotic perception and manipulation. By tackling the fundamental challenge of generalizing to unseen objects in real-world clutter, Romo’s research bridges the gap between controlled lab settings and practical, autonomous robotics. His contributions are pivotal for advancing applications in warehouse automation, domestic service robots, and industrial sorting, where adaptability and zero-shot learning are critical. Through his work, Romo has established himself as a key innovator in making robotic grasping more intelligent, flexible, and ready for real-world deployment.

Research Focus

Key Achievements

3
H-Index
3
Papers
706
Total Citations
235
Avg Citations/Paper
🏆 Most Cited Paper
Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching
461 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Massachusetts Institute of Technology

Top Papers

  1. 1
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago