Interactive teaching and experience extraction for learning about objects and robot activities
Interactive teaching and experience extraction for learning about objects and robot activities
复制标题
用于学习物体和机器人活动的交互式教学和经验提取
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
A. Tomé
中科院分区：
文献类型：
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作者：
G. H. Lim;Miguel Oliveira;V. Mokhtari;S. Kasaei;Aneesh Chauhan;L. Lopes;A. Tomé
智能服务机器人应该能够通过与环境，特别是与人类的持续互动，从积累的经验中提高知识。人类用户可以通过交互来指导经验获取、教授新概念或纠正不充分或错误的概念的过程。本文报告了以增量和开放式方式对物体和机器人活动进行交互式学习的工作。本文特别讨论了人机交互和经验收集。机器人的本体通过表示人机交互以及机器人体验的概念进行了扩展。人机交互本体不仅包括教师教学活动，还包括支持机器人适当反馈的机器人活动。针对不同类型的指令（包括触发机器人提取经验的示教指令）实现了两个简化的界面。这些机器人活动领域和感知领域的经验都被提取并存储在内存中，并用作学习方法的输入。上述功能完全集成在机器人架构中，并在 PR2 机器人中进行了演示。
Intelligent service robots should be able to improve their knowledge from accumulated experiences through continuous interaction with the environment, and in particular with humans. A human user may guide the process of experience acquisition, teaching new concepts, or correcting insufficient or erroneous concepts through interaction. This paper reports on work towards interactive learning of objects and robot activities in an incremental and open-ended way. In particular, this paper addresses human-robot interaction and experience gathering. The robot's ontology is extended with concepts for representing human-robot interactions as well as the experiences of the robot. The human-robot interaction ontology includes not only instructor teaching activities but also robot activities to support appropriate feedback from the robot. Two simplified interfaces are implemented for the different types of instructions including the teach instruction, which triggers the robot to extract experiences. These experiences, both in the robot activity domain and in the perceptual domain, are extracted and stored in memory, and they are used as input for learning methods. The functionalities described above are completely integrated in a robot architecture, and are demonstrated in a PR2 robot.