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Found 2 papers, 1 papers with code
Towards Inferring Users' Impressions of Robot Performance in Navigation Scenarios
As a more scalable and cost-effective alternative, we study the possibility of predicting people's impressions of robot behavior using non-verbal behavioral cues and machine learning techniques.
The EMPATHIC Framework for Task Learning from Implicit Human Feedback
We train a deep neural network on this data and demonstrate its ability to (1) infer relative reward ranking of events in the training task from prerecorded human facial reactions; (2) improve the policy of an agent in the training task using live human facial reactions; and (3) transfer to a novel domain in which it evaluates robot manipulation trajectories.
Human-Computer Interaction Robotics
