機械教育でロボット指導スキルを向上させる
Using Machine Teaching to Boost Novices' Robot Teaching Skill
機械教育アルゴリズムを用いて初心者をロボットの良い指導者に訓練する枠組みを提案し、訓練後も指導力が保持され、未訓練のスキルにも汎化することを実験で示した。
著者: Yuqing Zhu, Endong Sun, Matthew Howard
分類: cs.RO
原文アブストラクト
Recent evidence has shown that, contrary to expectations, it is difficult for users, especially novices, to teach robots tasks through LfD. This paper introduces a framework that leverages MT algorithms to train novices to become better teachers of robots, and verifies whether such teaching ability is retained beyond the period of training and generalises such that novices teach robots more effectively, even for skills for which training has not been received. A between-subjects study is reported, in which novice teachers are asked to teach simple motor skills to a robot. The results demonstrate that subjects that receive training show average 78.83% improvement in teaching ability (as measured by accuracy of the skill learnt by the robot), and average 63.69% improvement in the teaching of new skills not included as part of the training.
関連論文
- COACH: 協調ロボットティーチングロボット教育
