仮想観客インターフェースによる透明性向上を通じた人間-ロボットチームの訓練
Training Human-Robot Teams by Improving Transparency Through a Virtual Spectator Interface
人間-ロボットチームの事後レビュー用に、行動を視覚的に振り返る「仮想観客インターフェース」を提案し、チーム性能と状況認識への効果を検証した。
著者: Sean Dallas, Hongjiao Qiang, Motaz AbuHijleh, Wonse Jo, Kayla Riegner, Jon Smereka, Lionel Robert, Wing-Yue Louie, Dawn M. Tilbury
分類: cs.HC, cs.AI, cs.RO
原文アブストラクト
After-action reviews (AARs) are professional discussions that help operators and teams enhance their task performance by analyzing completed missions with peers and professionals. Previous studies that compared different formats of AARs have mainly focused on human teams. However, the inclusion of robotic teammates brings along new challenges in understanding teammate intent and communication. Traditional AAR between human teammates may not be satisfactory for human-robot teams. To address this limitation, we propose a new training review (TR) tool, called the Virtual Spectator Interface (VSI), to enhance human-robot team performance and situational awareness (SA) in a simulated search mission. The proposed VSI primarily utilizes visual feedback to review subjects' behavior. To examine the effectiveness of VSI, we took elements from AAR to conduct our own TR, designed a 1 x 3 between-subjects experiment with experimental conditions: TR with (1) VSI, (2) screen recording, and (3) non-technology (only verbal descriptions). The results of our experiments demonstrated that the VSI did not result in significantly better team performance than other conditions. However, the TR with VSI led to more improvement in the subjects SA over the other conditions.
