Longitudinal Robot Learning from Demonstration with Care Providers in a Home Environment
arXiv:2608.25196v1 Announce Type: new Abstract: Learning from demonstration (LfD) methods enable non-expert end users to teach robots novel skills without explicit programming. However most evaluations of the usability of LfD with non-experts has been conducted in controlled laboratory environments with a robotics experimenter present. In this work we identify non-expert end users' key barriers when teaching robots via demonstration without live robotics expert feedback in a home environment. In our human subjects experiment we support the non-expert end users through two forms of demonstrator guidance developed in prior work: pre-training and adaptive feedback. Towards the ecological validity of the evaluation, we conduct this experimentation over multiple visits, with a population of care providers. Finally, we propose to open source the resulting LfD dataset of care providers teaching a robot assistive tasks over multiple visits to a home environment.
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[Submitted on 25 Aug 2026]
Title:Longitudinal Robot Learning from Demonstration with Care Providers in a Home Environment
View a PDF of the paper titled Longitudinal Robot Learning from Demonstration with Care Providers in a Home Environment, by Nina Moorman and 8 other authors
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Abstract:Learning from demonstration (LfD) methods enable non-expert end users to teach robots novel skills without explicit programming. However most evaluations of the usability of LfD with non-experts has been conducted in controlled laboratory environments with a robotics experimenter present. In this work we identify non-expert end users' key barriers when teaching robots via demonstration without live robotics expert feedback in a home environment. In our human subjects experiment we support the non-expert end users through two forms of demonstrator guidance developed in prior work: pre-training and adaptive feedback. Towards the ecological validity of the evaluation, we conduct this experimentation over multiple visits, with a population of care providers. Finally, we propose to open source the resulting LfD dataset of care providers teaching a robot assistive tasks over multiple visits to a home environment.
Comments: ICRA 2026 Workshop on Bridging the Gap between Robot Learning and Human-Robot Interaction
Subjects:
Robotics (cs.RO); Human-Computer Interaction (cs.HC)
Cite as: arXiv:2608.25196 [cs.RO]
(or arXiv:2608.25196v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2608.25196
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Nina Moorman [view email] [v1] Tue, 25 Aug 2026 22:21:09 UTC (858 KB)
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