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pro vyhledávání: '"Florence, Peter R."'
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Com
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Com
Externí odkaz:
https://hdl.handle.net/1721.1/128398
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 101-110).
We present a method for ro
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 101-110).
We present a method for ro
Externí odkaz:
http://hdl.handle.net/1721.1/108982
What is the right object representation for manipulation? We would like robots to visually perceive scenes and learn an understanding of the objects in them that (i) is task-agnostic and can be used as a building block for a variety of manipulation t
Externí odkaz:
http://arxiv.org/abs/1806.08756
We would like robots to be able to safely navigate at high speed, efficiently use local 3D information, and robustly plan motions that consider pose uncertainty of measurements in a local map structure. This is hard to do with previously existing map
Externí odkaz:
http://arxiv.org/abs/1802.09076
Deep neural network (DNN) architectures have been shown to outperform traditional pipelines for object segmentation and pose estimation using RGBD data, but the performance of these DNN pipelines is directly tied to how representative the training da
Externí odkaz:
http://arxiv.org/abs/1707.04796
Publikováno v:
In Organic Electronics January 2013 14(1):411-415
Akademický článek
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Publikováno v:
2016 IEEE International Conference on Robotics & Automation (ICRA); 2016, p1469-1475, 7p