Enabling Embodied Human-Robot Co-Learning: Requirements, Method, and Test With Handover Task
Emma M. van Zoelen, Hugo Veldman-Loopik, Karel Van den Bosch, Mark A. Neerincx, David A. Abbink, Luka Peternel
- 发表年份
- 2024
- 引用次数
- 2
摘要
Despite a large body of research on robot learning, it has not yet been thoroughly studied how collaborating humans and robots learn reciprocally. In such situations, both humans and robots continuously learn about each other and the task through interaction. This letter addresses the research question: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">“How can human-robot co-learning be facilitated in physically embodied collaborative tasks?”</i>. First, we derived five requirements for successful human-robot co-learning from literature: shared goal, synchrony, interdependence, adaptability, and transparency. Based on these requirements, we designed a collaborative human-robot handover task and a robot Q-learning method. In an evaluation with six human participants co-learning was indeed found to emerge in the hand-over task. Particularly, for three of the human-robot dyads, our designed setup proved to facilitate co-learning in a way that met all five requirements. The task and robot learning method presented in this letter demonstrate how human-robot co-learning can be enabled in physically embodied tasks.
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