{'fraction_non_alphanumeric': 0.016815034619188922, 'fraction_numerical': 0.0, 'mean_word_length': 5.285714285714286, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Walking synchronously with a mobile robot using mutual rhythmic entrainement

Previously, we proposed a model that allows a robot to select an interacting partner and locates its focus of attention on the basis of synchrony between its own internal dynamics and the perceived visual stimuli. Here, we extend our approach for human-robot interactions in a "synchronous walking" scenario. Our inspirations comes from the notion of unintentional synchrony indicated by psychology and motor coordination studies as a fundamental parameter in social interactions. When two persons walk together, unconsciously, their steps are synchronized by constantly adjusting the length and the frequency of their steps. In this article, we are interested in replicating this human-human behavior in a robot-human interaction. we propose a neural network architecture that allows a robot to follow and walk synchronously with a human by adapting the robot's dynamic to the human gait using low level motor and visual primitives.