Probabilistic Models of Object Geometry with Application to Grasping
Robot manipulators typically rely on complete knowledge of object geometry in order to plan motions and compute grasps. But when an object is not fully in view it can be difficult to form an accurate estimate of the object's shape and pose, particularly when the object deforms. In this paper we...
Main Authors: | Rus, Daniela L. (Contributor), Glover, Jared (Contributor), Roy, Nicholas (Contributor) |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor) |
Format: | Article |
Language: | English |
Published: |
Sage Publications,
2010-09-29T14:42:08Z.
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Subjects: | |
Online Access: | Get fulltext |
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