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2022, Proceedings of the 9th Italian Workshop on Artificial Intelligence and Robotics (AIRO 2022), Pages -

Fall Detection using NAO Robot Pose Estimation in RoboCup SPL Matches (04b Atto di convegno in volume)

Zampino Cristian, Biancospino Flavio, Brienza Michele, Laus Francesco, Di Stefano Gianluca, Romano Rocchina, Pennisi Andrea, Suriani Vincenzo, Bloisi Domenico Daniele

RoboCup is an International robotics initiative whose aim is to promote robotics and AI research. RoboCup's long-term goal is to create a fully autonomous humanoid robot team capable of competing and winning a soccer game against the human World champion team, in compliance with the official rules of FIFA, by 2050. In this paper, we describe a two-step method for action recognition. In the first step, we extract the pose of the robots using a pose detector trained on a novel dataset for pose estimation called UNIBAS NAO Pose Dataset, which is a contribution of this work. In the second step, a Spatial-Temporal Graph Convolutional Network is used for modeling the gameplay, with particular regard to fall-down detection. Experimental results show the effectiveness of our approach in detecting falls for humanoid robots.
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