Longitudinal Robot Learning from Demonstration with Care Providers in a Home Environment

2026-08-25

AI Summary

研究通过多访家庭环境实验，采用预训练和自适应反馈方法解决非专家用户在无现场机器人专家指导情况下教导机器人的障碍。

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.

Problem

• Learning from Demonstration
• non-expert users
• home environment
• care providers

Innovation

• Learning from Demonstration (LfD)
• non-expert users
• demonstrator guidance
• home environment
• open source LfD dataset