Learning and Interactive Design of Shared Control Templates

Abstract

Controlling a robotic arm to achieve manipulation tasks is challenging for humans. Especially if only low-dimensional input signals can be provided, as is often the case for users with motor impairments. Using shared control to provide task-specific guidance and constraints facilitates control -- for instance with the Shared Control Templates (SCT) framework -- and enables even complex activities of daily living to be performed successfully. However, designing SCTs is a laborious task requiring robotic expertise. To make such design easier and faster, we propose a method for semi-automatically designing SCTs on the basis of demonstrations. Furthermore, we propose two similarity metrics, and demonstrate how these can be used to transfer knowledge from one SCT to another. We demonstrate that the SCTs so acquired can be successfully used in shared control for everyday tasks such as opening a drawer or a cupboard on our assistive robot EDAN.