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. © 2022 Copyright for this paper by its authors.
Fall Detection using NAO Robot Pose Estimation in RoboCup SPL Matches
Domenico Daniele
2023-01-01
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. © 2022 Copyright for this paper by its authors.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
