Helping Robots Imitate: Metrics And Computational Solutions Inspired By Human-Robot Interaction Studies
Helping Robots Imitate: Metrics And Computational Solutions Inspired By Human-Robot Interaction Studies
复制标题
帮助机器人模仿：受人机交互研究启发的指标和计算解决方案
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
C. Nehaniv
中科院分区：
文献类型：
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作者：
A. Alissandrakis;N. Otero;J. Saunders;K. Dautenhahn;C. Nehaniv
在本章中，我们将介绍与帮助机器人模仿人类相关的三个研究方向。这些研究基于观察到的人类行为、技术指标和实施的技术解决方案。这三条研究路线是：（a）一些用户研究，显示人类如何自然地倾向于展示机器人学习的任务，（B）一种正式的方法来解决机器人应该模仿什么的问题，以及（c）一种技术驱动的概念框架和技术，受到社会学习理论的启发，解决了如何教机器人。在这个合并练习中，我们将尝试提出一种方法，通过这个问题的空间，对设计一个人-机器人交互（HRI）系统，能够通过演示教人。
In this chapter we describe three lines of research related to the issue of helping robots imitate people. These studies are based on observed human be- haviour, technical metrics and implemented technical solutions. The three lines of research are: (a) a number of user studies that show how humans naturally tend to demonstrate a task for a robot to learn, (b) a formal approach to tackle the problem of what a robot should imitate, and (c) a technology-driven conceptual framework and technique, inspired by social learning theories, that addresses how a robot can be taught. In this merging exercise we will try to propose a way through this prob- lem space, towards the design of a Human-Robot Interaction (HRI) system able to be taught by humans via demonstration.