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Extraction of commonsense knowledge for “Bring something” robotic service at home

机译:提取常识知识,以在家中“带点东西”机器人服务

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Sharing commonsense knowledge is one key to realize symbiosis between human and robot. However, as human knowledge is so complicated, it is difficult to extract appropriate information for robot. This paper presents our approach to extract the core part from Basic-level Knowledge Network (BKN) to be used for intuitive “Bring something” robotic service. A two-step filtering method was implemented based on the weighting mechanism of BKN. The first step used one weighting parameter to filter the most irrelevant data. The second step combined all weighting parameters from BKN with user response data from a questionnaire to estimate commoness of object-activity connections. Result showed that the proposed approach is efficient to extract the most common activities related to each object in BKN, therefore to help robot understands human intention and provide intuitive service.
机译:共享常识知识是实现人机共生的关键之一。然而,由于人类知识是如此复杂,因此难以为机器人提取适当的信息。本文介绍了我们从基础知识网络(BKN)中提取核心部分的方法,该方法可用于直观的“带来一些”机器人服务。基于BKN的加权机制,实现了两步滤波方法。第一步使用一个加权参数来过滤最不相关的数据。第二步将来自BKN的所有加权参数与来自问卷的用户响应数据相结合,以估计对象与活动之间的联系。结果表明,该方法能有效提取与BKN中每个对象有关的最常见活动,从而有助于机器人理解人的意图并提供直观的服务。

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