Rod Grupen
Papers
9
Total Citations
128
H-Index
6
About
Rod Grupen’s research lies at the intersection of robotics, machine learning, and human-robot interaction, with a focus on enabling autonomous systems to learn complex, hierarchical behaviors. His major contributions include pioneering frameworks for intrinsically motivated learning, where robots are driven by curiosity to build deep control knowledge and manipulation skills incrementally. His work on “Intrinsically motivated hierarchical manipulation” (32 citations) and “A Framework for Learning Declarative Structure” (19 citations) demonstrates how robots can autonomously acquire sophisticated sensorimotor capabilities without explicit programming. Grupen also advanced the concept of “logical behaviors” (19 citations), which integrates multisensory data around egocentric tasks, and explored how manipulation skills can naturally evolve into communicative gestures. His research on mobile, dexterous social robots (32 citations) has influenced the design of robots capable of both physical interaction and social engagement. More recently, he has applied convolutional neural networks to object manipulation and studied human-robot teams in emergency response scenarios. Grupen’s work is notable for its emphasis on lifelong learning and skill transfer, providing foundational principles for building robots that adapt and improve through experience.
Research Focus
Key Achievements
Top Papers
- 1
- 2Intrinsically motivated hierarchical manipulation32 citations · 2008
- 3Logical behaviors19 citations · 1990
- 4A Framework for Learning Declarative Structure19 citations · 2006
- 5Hierarchical skills and skill-based representation9 citations · 2011
- 6
- 7Choosing informative actions for manipulation tasks3 citations · 2011
- 8
- 9From manipulation to communicative gesture2 citations · 2010