Fall Risk Reduction for the Elderly Using Mobile Robots Based on the Deep Reinforcement Learning

被引：0

作者：

Namba, Takaaki ^{[1
]}

Yamada, Yoji ^{[1
]}

机构：

[1] Nagoya Univ, Grad Sch Engn, Chikusa Ku, Furo Cho, Nagoya, Aichi 4648603, Japan

来源：

ICAROB 2017: PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS | 2017年

关键词：

Safety; Risk Reduction; Mobile Robot; Deep Learning; Reinforcement Learning;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Slip-induced fall is one of the main factors causing serious fracture among the elderly. This paper proposes a deep learning based fall risk reduction measures by mobile assistant robots for the elderly. We use a deep convolutional neural network to analyze fall risks. We apply a deep reinforcement learning to control robots and reduce slip-induced fall risks of the elderly. The results suggest that the applicability of our method to other cases of the fall and other cases of accidents.

引用

页码：P571 / P574

页数：4

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