Real-Time Multimodal Signal Processing for HRI in RoboCup: Understanding a Human Referee
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.
Keywords
Cite
@article{arxiv.2411.17347,
title = {Real-Time Multimodal Signal Processing for HRI in RoboCup: Understanding a Human Referee},
author = {Filippo Ansalone and Flavio Maiorana and Daniele Affinita and Flavio Volpi and Eugenio Bugli and Francesco Petri and Michele Brienza and Valerio Spagnoli and Vincenzo Suriani and Daniele Nardi and Domenico D. Bloisi},
journal= {arXiv preprint arXiv:2411.17347},
year = {2024}
}
Comments
11th Italian Workshop on Artificial Intelligence and Robotics (AIRO 2024), Published in CEUR Workshop Proceedings AI*IA Series