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

本研究的目的是实现一个系统，允许普通人，没有特别的知识，对机器人，教动作人形机器人通过触摸他们。选择聚焦于类人机器人是出于两个主要原因。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，而无需构建新的工具和基础设施。第二，如果适当地编程，它们的行为可以很容易地被人们理解。事实上，人类已经能够熟练地预测他人的行为。如果机器人的动作与人类相似，那么人们将能够无意识地预测机器人的行为。这反过来又简化了人类和机器人之间的交流，并增加了两者的安全性。研究人员调查了普通人在触摸人形机器人时期望它做出的动作。根据收集的数据，建立了这些响应的数学模型。机器人根据模型进行了运动，并验证了人们对机器人运动的自然性。此外，它表明，给定触摸的几个响应，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反应分为几组，这与普通人倾向于做的分组相对应。这项工作目前正在审查中。为了更深入地研究头部的预期运动，还开发了一种新的4DOF机器人头部。该机制的研究具有重要的理论意义，并导致在Journal of Mechanisms and Machine Theory上发表。此外，对多个噪声传感器信息集成的考虑导致在非线性科学和数值模拟杂志上的另一个理论出版物。

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.