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.
Fall Detection using NAO Robot Pose Estimation in RoboCup SPL Matches / Zampino, Cristian; Biancospino, Flavio; Brienza, Michele; Laus, Francesco; Di Stefano, Gianluca; Romano, Rocchina; Pennisi, Andrea; Suriani, Vincenzo; Bloisi, Domenico Daniele. - (2022), pp. 88-95. (Intervento presentato al convegno 9th Italian Workshop on Artificial Intelligence and Robotics (AIRO 2022) tenutosi a Udine; Italia).
Fall Detection using NAO Robot Pose Estimation in RoboCup SPL Matches
Andrea Pennisi;Vincenzo Suriani;Domenico Daniele Bloisi
2022
Abstract
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.File | Dimensione | Formato | |
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