A Method for Embodied Co-Learning in Interdependent Human-Robot Teams

A Method for Embodied Co-Learning in Interdependent Human-Robot Teams

Loopik, Hugo (TU Delft Mechanical, Maritime and Materials Engineering)

Peternel, L. (mentor)
van Zoelen, E.M. (mentor)
Abbink, D.A. (mentor)

Delft University of Technology

Delft University of Technology

Mechanical Engineering

2023-07-06

This paper addresses the research question: “How can a human-robot team achieve co-learning, and interdependence in physically embodied tasks?”
A method has been developed that enables a human-robot team to co-learn the handover of an object from the robot to the human. Five design requirements were composed to address the challenges of human-robot co-learning in physically embodied environments. The method is based on a Q-learning algorithm that was adapted and extended to meet these requirements. An experiment was conducted with six participants. For every human-robot team, each design requirement was qualitatively evaluated. Interdependent co-learning was identified in three of the six teams. The limitation of the design, and how this method can be improved further, was discussed. The method, presented in this paper, demonstrates how human-robot co-learning and interdependence can be enabled in physically embodied tasks.

Co-Learning
Human-Robot Collaboration
Reinforcement Learning (RL)
Handover
Interdependence
Human-Robot Interaction
Q-Learning

http://resolver.tudelft.nl/uuid:acc0e5c9-8434-4b22-8d7d-50b1d4917063

Student theses

master thesis

© 2023 Hugo Loopik