Ontology-Based User Intention Recognition for Proactive Planning of Intelligent Robot Behavior

Hochul Jeon, Taehwan Kim, Joongmin Choi
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引用次数: 28

Abstract

To recognize user intention proactively and do a suitable action or service are one of important issues in intelligent robot. Even when a user acts the same behavior, its intention may be different according to the user's context. It means that user intention recognition involves the uncertainties, and by minimizing the uncertainties can improve the accuracy of the user intention recognition. This paper suggests a novel ontology-based approach for user intention recognition. We propose a method of minimizing the uncertainties that are the main obstacles against the precise recognition of user intention. This approach creates an ontology for user intention, makes a hierarchy and relationship among user intentions, and precisely recognizes user intention by using the gathered sensor data such as temperature, humidity, vision, and auditory. We developed a simulator that evaluates the performance of robot proactive planning mechanism.
基于本体的智能机器人行为主动规划用户意图识别
主动识别用户意图并做出相应的动作或服务是智能机器人的重要问题之一。即使用户做出了相同的行为,其意图也可能根据用户的上下文而有所不同。这意味着用户意图识别涉及到不确定性,通过最小化不确定性可以提高用户意图识别的准确性。提出了一种基于本体的用户意图识别方法。我们提出了一种最小化不确定性的方法,这些不确定性是精确识别用户意图的主要障碍。该方法建立用户意图本体,建立用户意图之间的层次关系,利用采集到的温度、湿度、视觉、听觉等传感器数据对用户意图进行精确识别。我们开发了一个评估机器人主动规划机制性能的模拟器。
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