期刊
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
卷 -, 期 -, 页码 7834-7841出版社
IEEE
DOI: 10.1109/iros40897.2019.8968106
关键词
-
类别
资金
- [688147]
Reasoning about spatial and geometric relations between objects in a tabletop human-robot interaction is a challenge due to the perception not being always consistent: objects placed on a table seem to be slightly in the air; they overlap; they disappear due to occlusions. Yet, interpreting and anchoring perceptual data in a physically consistent estimation of the scene is a crucial ability for humans, and thus robots in HRI context. In this paper we present a simulation-based physics reasoner integrated in a lightweight situation-assessment framework called Underworlds, that allows the robot to stabilize objects and build at run-time a consistent estimation of the scene, even for entirely hidden objects, while inferring the actions performed by its human partner.
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