伙伴机器人人体状态模式获取方法研究

2021 International Symposium on Micro-NanoMehatronics and Human Science (MHS) Pub Date : 2021-12-05 DOI:10.1109/mhs53471.2021.9767168

Nao Yamada, Mohamad Yani, N. Kubota

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引用次数: 0

摘要

对于一个支持人的伙伴机器人来说，了解人在环境中的状态模式是很重要的，这样机器人才能根据状态产生个性化的运动。在本研究中，我们研究了一种人体状态分类方法，使系统能够获取难以预先设计的人体状态模式。结果表明，使用人类骨骼信息和基于密度的聚类，状态分类是可能的。

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A Study of Human State Pattern Acquisition Method for Partner Robots

For a partner robot that supports a human, it is important to know the state pattern of the human in the environment so that the robot can generate personalized motions according to the state. In this study, we studied a human state classification method to enable the system to acquire human state patterns, which are difficult to design in advance. As a result, we showed that state classification is possible using human skeletal information and density-based clustering.

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2021 International Symposium on Micro-NanoMehatronics and Human Science (MHS)

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