论文标题
知道在哪里看：一种基于计划的体系结构来自动化社交机器人的目光
Knowing Where to Look: A Planning-based Architecture to Automate the Gaze Behavior of Social Robots
论文作者
论文摘要
凝视提示在人类交流中起着重要的作用，并用于协调转折和关注的关注，并调节亲密关系。为了与人进行流利的对话，社交机器人需要表现出类似人类的凝视行为。 HRI中先前的注视控制系统（GCS）使用数据驱动或启发式方法自动化了机器人注视。但是，这些系统本质上主要是反应性的。提前计划机器人凝视可以帮助实现更现实的凝视行为和更好的眼头协调。在本文中，我们建议并实施一种基于计划的新型GC。我们在反应性系统和提出的系统之间的对象内用户研究（n = 26）中评估了我们的系统。结果表明，用户更喜欢拟议的系统，并且在调节亲密关系方面更容易解释和更好。
Gaze cues play an important role in human communication and are used to coordinate turn-taking and joint attention, as well as to regulate intimacy. In order to have fluent conversations with people, social robots need to exhibit human-like gaze behavior. Previous Gaze Control Systems (GCS) in HRI have automated robot gaze using data-driven or heuristic approaches. However, these systems tend to be mainly reactive in nature. Planning the robot gaze ahead of time could help in achieving more realistic gaze behavior and better eye-head coordination. In this paper, we propose and implement a novel planning-based GCS. We evaluate our system in a comparative within-subjects user study (N=26) between a reactive system and our proposed system. The results show that the users preferred the proposed system and that it was significantly more interpretable and better at regulating intimacy.
