Abstract
In this paper, we investigate physical human–robot interaction (PHRI) as an important extension of traditional HRI research. The aim of this research is to develop a motor learning system that uses physical help from a human helper. We first propose a new control system that takes advantage of inherent joint flexibility. This control system is applied on a new humanoid robot called CB2. In order to clarify the difference between successful and unsuccessful interaction, we conduct an experiment where a human subject has to help the CB2robot in its rising-up motion. We then develop a new measure that demonstrates the difference between smooth and non-smooth physical interactions. An analysis of the experiment’s data, based on the introduced measure, shows significant differences between experts and beginners in human–robot interaction.
Highlights
IntroductionMany researchers have been focusing on generating robot motions by learning
In recent years, many researchers have been focusing on generating robot motions by learning
We investigated physical human–robot interaction (PHRI) as an important extension of traditional Human–Robot Interaction (HRI) research
Summary
Many researchers have been focusing on generating robot motions by learning. It is difficult to generate real robot motion due to the noise in real environment or breakdowns of the robot’s hardware during the many trials required for learning. In order to realise this kind of learning scheme, the class of Human–Robot Interaction (HRI) where a human and a robot are influencing each other by physical contacts has to be considered. An analysis method for the physical interaction has not been established because the interactions considered in the existing studies have been focusing on symbolic communications that usually assume turn-taking. We study this type of HRI in order to clarify the requirements of robot hardware and software by implementing an example behaviour and analyse the realised behaviour in order to figure out how to evaluate physical interaction behaviours. We denote the class of HRI considered in this research as physical human–robot interaction (PHRI)
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