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We present ProxEmo, a novel end-to-end emotion prediction algorithm forsocially aware robot navigation among pedestrians. Our approach predicts theperceived emotions of a pedestrian from walking gaits, which is then used foremotion-guided navigation taking into account social and proxemic constraints.To classify emotions, we propose a multi-view skeleton graph convolution-basedmodel that works on a commodity camera mounted onto a moving robot. Our emotionrecognition is integrated into a mapless navigation scheme and makes noassumptions about the environment of pedestrian motion. It achieves a meanaverage emotion prediction precision of 82.47% on the Emotion-Gait benchmarkdataset. We outperform current state-of-art algorithms for emotion recognitionfrom 3D gaits. We highlight its benefits in terms of navigation in indoorscenes using a Clearpath Jackal robot.

ProxEmo: Gait-based Emotion Learning and Multi-view Proxemic Fusion for Socially-Aware Robot Navigation