脳信号からユーザの軌道選好を学習する
Learning User Preferences for Trajectories from Brain Signals
ロボットアームの軌道を観察中の脳波（EEG）を用いてユーザの選好を解読し、軌道を好み順にランク付けできることを示した研究。
著者: Henrich Kolkhorst, Wolfram Burgard, Michael Tangermann
分類: cs.RO, cs.HC, cs.LG, stat.ML
原文アブストラクト
Robot motions in the presence of humans should not only be feasible and safe, but also conform to human preferences. This, however, requires user feedback on the robot's behavior. In this work, we propose a novel approach to leverage the user's brain signals as a feedback modality in order to decode the judgment of robot trajectories and rank them according to the user's preferences. We show that brain signals measured using electroencephalography during observation of a robotic arm's trajectory as well as in response to preference statements are informative regarding the user's preference. Furthermore, we demonstrate that user feedback from brain signals can be used to reliably infer pairwise trajectory preferences as well as to retrieve the preferred observed trajectories of the user with a performance comparable to explicit behavioral feedback.
