Papers
2
Total Citations
21
H-Index
2
About
Constantin Uhde’s research lies at the intersection of cognitive robotics, causal reasoning, and human-robot interaction, with a focus on enabling robots to understand and act purposefully in complex environments. His major contributions center on developing methods for robots to learn causal relationships from human demonstrations and self-supervised intervention, allowing them to infer the necessary sequence of actions—like opening a cupboard before grasping an object inside. In his highly cited work, “The Robot as Scientist” (2020, 17 citations), Uhde pioneered the use of mental simulation in virtual reality to test causal hypotheses extracted from human activities, effectively turning the robot into an active experimenter. His subsequent work (2022, 4 citations) advanced affordance learning, enabling robots to generalize causal knowledge about object properties to unfamiliar environments—a critical step toward robust, transferable robotic intelligence. These contributions are notable for bridging cognitive science and robotics, offering a principled framework for purposeful action. Uhde’s research is essential reading for anyone interested in how robots can move beyond scripted behaviors to become true causal learners.
Research Focus
Key Achievements
Top Papers
- 1
- 2