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Meaningful maps with object-oriented semantic mapping | IEEE Conference Publication | IEEE Xplore

Meaningful maps with object-oriented semantic mapping


Abstract:

For intelligent robots to interact in meaningful ways with their environment, they must understand both the geometric and semantic properties of the scene surrounding the...Show More

Abstract:

For intelligent robots to interact in meaningful ways with their environment, they must understand both the geometric and semantic properties of the scene surrounding them. The majority of research to date has addressed these mapping challenges separately, focusing on either geometric or semantic mapping. In this paper we address the problem of building environmental maps that include both semantically meaningful, object-level entities and point- or mesh-based geometrical representations. We simultaneously build geometric point cloud models of previously unseen instances of known object classes and create a map that contains these object models as central entities. Our system leverages sparse, feature-based RGB-D SLAM, image-based deep-learning object detection and 3D unsupervised segmentation.
Date of Conference: 24-28 September 2017
Date Added to IEEE Xplore: 14 December 2017
ISBN Information:
Electronic ISSN: 2153-0866
Conference Location: Vancouver, BC, Canada

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