MANNERS-DB
收藏arXiv2020-07-24 更新2024-08-06 收录
下载链接：
http://arxiv.org/abs/2007.12506v1
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资源简介：
MANNERS-DB是由剑桥大学计算机科学与技术系创建的数据集，专注于评估家用机器人行为的社交适宜性。该数据集包含1000个模拟家庭场景，每个场景中的机器人行为均由人类标注其社交适宜性。数据集通过Unity3D模拟软件生成，确保了场景配置的多样性和控制性。MANNERS-DB旨在通过机器学习模型预测机器人行为的社交适宜性，推动机器人更好地理解和适应社交环境，解决机器人在复杂社交环境中行为适宜性的问题。
MANNERS-DB is a dataset developed by the Department of Computer Science and Technology at the University of Cambridge, which focuses on evaluating the social appropriateness of home robot behaviors. This dataset comprises 1000 simulated home scenarios, in each of which the social appropriateness of robot behaviors is annotated by human raters. Generated via the Unity3D simulation software, the dataset guarantees the diversity and controllability of scenario configurations. The core goal of MANNERS-DB is to predict the social appropriateness of robot behaviors using machine learning models, so as to advance robots' ability to better understand and adapt to social environments and resolve the problem of behavioral appropriateness of robots in complex social settings.
提供机构：
剑桥大学计算机科学与技术系
创建时间：
2020-07-24
