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arXiv · 2411.17347

Real-Time Multimodal Signal Processing for HRI in RoboCup: Understanding a Human Referee

Filippo Ansalone·Flavio Maiorana·Daniele Affinita·Flavio Volpi·Eugenio Bugli·Francesco Petri·Michele Brienza·Valerio Spagnoli·Vincenzo Suriani·Daniele Nardi·Domenico D. Bloisi
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Abstract

Advancing human-robot communication is crucial for autonomous systems operating in dynamic environments, where accurate real-time interpretation of human signals is essential. RoboCup provides a compelling scenario for testing these capabilities, requiring robots to understand referee gestures and whistle with minimal network reliance. Using the NAO robot platform, this study implements a two-stage pipeline for gesture recognition through keypoint extraction and classification, alongside continuous convolutional neural networks (CCNNs) for efficient whistle detection. The proposed approach enhances real-time human-robot interaction in a competitive setting like RoboCup, offering some tools to advance the development of autonomous systems capable of cooperating with humans.

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Filippo Ansalone, Flavio Maiorana, Daniele Affinita, Flavio Volpi, Eugenio Bugli, Francesco Petri, Michele Brienza, Valerio Spagnoli, Vincenzo Suriani, Daniele Nardi, Domenico D. Bloisi. 2024-11-26. Real-Time Multimodal Signal Processing for HRI in RoboCup: Understanding a Human Referee. https://arxiv.org/abs/2411.17347

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