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物理的インタラクションに基づくヒューマノイドロボットへの直感的な全身運動の教示

基于物理交互的人形机器人直观全身运动教学

基本信息

批准号：
12F02048
负责人：
石黒浩
金额：
$ 1.47万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for JSPS Fellows
财政年份：
2012
资助国家：
日本
起止时间：
2012 至 2013
项目状态：
已结题

项目摘要

The purpose of this research is the realization of a system that allows ordinary people, with no particular knowledge on robots, to teach motions to humanoid robots by touching them. The choice of focusing on humanoids is motivated by two main reasons. First, humanoid robots have a morphology similar to the one of people, and are thus expected to be able to use tools and infrastructures already available for people, without the need of building new ones. Second, if opportunely programmed, their actions can be easily understood by people. Indeed, humans are already skilled in predicting other people's behavior. If robots move similarly to humans, then people will be able to unconsciously predict robot's behaviors. This in turn, eases the communication between humans and robots and increases the safety of both of them.The movements that ordinary people expect from a humanoid robot when they touch it were investigated. From the data collected a mathematical model of these responses was created. The robot was moved according to the model, and it was verified that people find the robot movements natural. Moreover, it was shown that, given several responses to a touch, the model is able to predict which is the most natural one. The model was also shown to be able to classify the responses into several groups, which correspond to the grouping that ordinary people tend to do. The work is currently under review.In order to study with more depth the expected movements of the head, a new 4DOF robotics head was also developed. The study of this mechanism has important theoretical implications, and led to a publication in the Journal of Mechanisms and Machine Theory.Additionally, considerations on the integration of information from multiple noisy sensors lead to another theoretical publication in the Communications in Nonlinear Science and Numerical Simulations Journal.

这项研究的目的是实现一个系统，允许普通人，对机器人没有特别的知识，通过触摸类人机器人来教他们动作。选择专注于类人生物有两个主要原因。首先，类人机器人具有与人类相似的形态，因此预计能够使用人类已有的工具和基础设施，而不需要建造新的工具和基础设施。其次，如果编程得当，他们的行为很容易被人们理解。事实上，人类已经很擅长预测别人的行为了。如果机器人的动作与人类相似，那么人们将能够在不知不觉中预测机器人的行为。这反过来又简化了人类和机器人之间的交流，增加了两者的安全性。研究人员调查了普通人在触摸类人机器人时期望它的动作。根据收集的数据，建立了这些反应的数学模型。根据模型对机器人进行了移动，验证了人们对机器人动作的自然而然。此外，研究表明，在给定对触摸的几个反应的情况下，该模型能够预测哪一个是最自然的。该模型还被证明能够将回答分成几个组，这与普通人倾向于进行的分组相对应。为了更深入地研究头部的预期运动，还开发了一种新的四自由度机器人头部。对这一机制的研究具有重要的理论意义，并导致在《机构与机器理论》杂志上发表了一篇文章。此外，对来自多个噪声传感器的信息的整合的考虑导致了另一篇理论文章发表在《非线性科学与数值模拟通讯》杂志上。