Abstract

In this study, we propose a deep learning based- social activities recognition algorithm for socially aware mobile robot navigation framework. The proposed method utilizes the OpenPose library and the Long-short term memory deep learning neural network, which observes the human skeleton in some time steps, then predicts that the human social activities including human running, walking, standing, sitting and laying. We train and test the proposed deep learning neural network model on a dataset that we synthesize. The experimental results illustrate that our proposed method can predict the human social activities with higher accuracy.

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