ロボット仲介タスクのための展開可能アーキテクチャDART:社会的支援ロボットによる認知行動療法エクササイズでの評価
A Deployable Architecture for Robot-Mediated Tasks (DART): Evaluation in Socially Assistive Robot-Guided Cognitive Behavioral Therapy Exercises
低コストな社会的支援ロボットをWebアプリとクラウドで拡張するアーキテクチャDARTを提案し、大学生の不安軽減のためのCBT宿題支援システムに実装して、実験室と6週間の家庭内展開で有効性とユーザビリティを評価した。
詳しい要約
1. どんなもの?
2. 先行研究と比べてどこがすごい?
3. 技術・手法の肝は?
4. どうやって有効だと検証した?
5. 議論はある?
6. 次に読むべき論文は?
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著者: Mina Kian, Lydia Ignatova, Jiong Wang, Ji Min Lee, Jiancheng Li, Qianwei Guo, Emily Weiss, Amy O'Connell, Kaitlin Zareno, Jiani Li, Reyna Patel, Leyaa George, Minyu Huang, Justin Yang, Maja J. Matarić
分類: cs.RO
原文アブストラクト
Socially assistive robots (SARs) can support structured health and well-being interventions, but hardware and cost constraints limit interaction complexity and longitudinal real-world deployments. We present DART: Deployable Architecture for Robot-Mediated Tasks, an architecture that extends SARs through a web application and cloud infrastructure, enabling visual content, user input, remote computation, and persistent data storage synergistically with the robot's physical embodiment, speech, and movement. We evaluated DART by instantiating it in an interatively-developed full-stack HRI system for helping university students with elevated generalized anxiety to complete cognitive behavioral therapy (CBT) homework exercises. The resulting system, which used the low-cost open-source Blossom robot platform, was refined and evaluated through a participatory design process and multiple user studies, and finally evaluated in an in-lab study with 103 participants, and then a six-week in-home deployment with four participants. In the in-lab evaluation, participants showed significant within-session reductions in stress, state anxiety, and negative affect, and gave the platform a mean System Usability Scale score of 78.89. In the home deployment, the mean System Usability Scale score was 87.5, with positive qualitative feedback on usability. Participants across both groups identified speech input, visual presentation, and web-robot synchronization as priorities for improvement. These findings validate DART as an effective architecture for extending the capabilities of a low-cost SAR in both in-lab single-session and in real-world longitudinal deployments.