Learning robot motor skills with mixed realityDownload PDF

18 Feb 2022, 16:58 (modified: 01 Jul 2022, 18:53)VAM-HRI 2022Readers: Everyone
Keywords: robot learning, mixed reality, human-robot interaction
TL;DR: We address the research problem of incorporating four types of complex world knowledge into a single motor skill learning framework with Mixed Reality
Abstract: Mixed Reality (MR) has recently shown great success as an intuitive interface for enabling end-users to teach robots. Related works have used MR interfaces to communicate robot intents and beliefs to a co-located human, as well as developed algorithms for taking multi-modal human input and learning complex motor behaviors. Even with these successes, enabling end-users to teach robots complex motor tasks still poses a challenge because end-user communication is highly task dependent and world knowledge is highly varied. We propose a learning framework where end-users teach robots a) motion demonstrations, b) task constraints, c) planning representations, and d) object information, all of which are integrated into a single motor skill learning framework based on Dynamic Movement Primitives (DMPs). We hypothesize that conveying this world knowledge will be intuitive with an MR interface, and that a sample-efficient motor skill learning framework which incorporates varied modalities of world knowledge will enable robots to effectively solve complex tasks.
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