The Emotionally Intelligent Robot: Improving Social Navigation in Crowded Environments [article]

Aniket Bera and Tanmay Randhavane and Rohan Prinja and Kyra Kapsaskis and Austin Wang and Kurt Gray and Dinesh Manocha
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
more » ... aracteristics into four emotion categories (happy, sad, angry, neutral). In our validation results, we observe an emotion detection accuracy of 85.33%. We formulate emotion-based proxemic constraints to perform socially-aware robot navigation in low- to medium-density environments. We demonstrate the benefits of our algorithm in simulated environments with tens of pedestrians as well as in a real-world setting with Pepper, a social humanoid robot.
arXiv:1903.03217v1 fatcat:itkqg5irm5fn3klijh2uwkabku