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Preview of https://www.ijcai.or g/proceedings/2018/0 266.pdf
🔗 Source: ijcai.org
📊 Size: 1.11 MB
👤 Author: Tiago Mota, Mohan Sridharan
⬇️ Downloads: 287

Summary

The architecture uses Answer Set Prolog to represent and reason with spatial relations, and combines non-monotonic logical inference, Qualitative Spatial Representations (QSR), and Metric Spatial Representations (MSR) to infer spatial relations between 3D point clouds. It starts with a generic grounding of prepositions and incrementally learns a specialized grounding from experience and feedback, allowing robots to infer spatial relations, acquire a specialized grounding, and determine the relative confidence in each grounding. The architecture is evaluated on a benchmark dataset of tabletop images and complex simulated scenes of furniture.

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The architecture uses Answer Set Prolog to represent and reason with spatial relations, and combines non-monotonic logical inference, Qualitative Spatial...

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  • File Format: PDF
  • File Size: 1.11 MB
  • Pages: 7
  • Language: EN
  • Author: Tiago Mota, Mohan Sridharan
  • Total Downloads: 287
  • Last Updated: 5 hours ago

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