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The Emotionally Intelligent Robot: Improving Social Navigation in Crowded Environments
[article]
2019
arXiv
pre-print
We present a real-time algorithm for emotion-aware navigation of a robot among pedestrians. Our approach estimates time-varying emotional behaviors of pedestrians from their faces and trajectories using a combination of Bayesian-inference, CNN-based learning, and the PAD (Pleasure-Arousal-Dominance) model from psychology. These PAD characteristics are used for long-term path prediction and generating proxemic constraints for each pedestrian. We use a multi-channel model to classify pedestrian
arXiv:1903.03217v1
fatcat:itkqg5irm5fn3klijh2uwkabku