Papers

8

Total Citations

88

H-Index

6

About

Constantin A. Rothkopf is a leading researcher at the intersection of robotics, cognitive science, and human-robot interaction, with a primary focus on enabling robots to learn from and adapt to human partners. His work centers on making robot behavior intuitive and safe for non-experts through imitation learning and interactive reinforcement learning. A key contribution is the development of intention-aware movement primitives that allow robots to anticipate and react to human co-workers in real-time, a concept detailed in his highly cited 2019 paper (38 citations). He has also pioneered methods for integrating multimodal human feedback—combining speech, gestures, and other cues—to accelerate robot learning, as seen in his 2022 work on Bayesian fusion of advice. Rothkopf’s research extends to active tactile perception for texture recognition and the computational modeling of human sensorimotor control, including how we integrate visual and auditory cues for depth estimation. His involvement in the IM-CLeVeR project on intrinsically motivated learning further underscores his commitment to building versatile, autonomous systems that learn cumulatively from their environment and human interaction.

Research Focus

Key Achievements

6
H-Index
8
Papers
88
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Learning Intention Aware Online Adaptation of Movement Primitives
38 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 47
🏛 Institutions: Technische Universität Darmstadt, Goethe University Frankfurt, Frankfurt Institute for Advanced Studies

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago