Physical human-robot interaction: Mutual learning and adaptation

Shuhei Ikemoto, Heni Ben Amor, Takashi Minato, Bernhard Jung, Hiroshi Ishiguro

Research output: Contribution to journalArticle

74 Scopus citations

Abstract

Close physical interaction between robots and humans is a particularly challenging aspect of robot development. For successful interaction and cooperation, the robot must have the ability to adapt its behavior to the human counterpart. Based on our earlier work, we present and evaluate a computationally efficient machine learning algorithm that is well suited for such close-contact interaction scenarios. We show that this algorithm helps to improve the quality of the interaction between a robot and a human caregiver. To this end, we present two human-in-the-loop learning scenarios that are inspired by human parenting behavior, namely, an assisted standing-up task and an assisted walking task.

Original languageEnglish (US)
Article number6161710
Pages (from-to)24-35
Number of pages12
JournalIEEE Robotics and Automation Magazine
Volume19
Issue number4
DOIs
StatePublished - 2012

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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