家庭環境における介護者との縦断的ロボット学習：デモンストレーションからの学習
Longitudinal Robot Learning from Demonstration with Care Providers in a Home Environment
家庭環境で非専門家の介護者がロボットにタスクを教える際の障壁を特定し、事前訓練と適応的フィードバックによる支援の効果を複数回の訪問を通じて評価した。
著者: Nina Moorman, Julianna Schalkwyk, Vriksha Srihari, Qingyu Xiao, Kamel Alrashedy, Hongseok Jeong, Kiersten Lange, Matthew B. Luebbers, Matthew Gombolay
分類: cs.RO, cs.HC
原文アブストラクト
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.