Robots can move, see, and navigate in the real world outside carefully structured factories, but they cannot yet grasp and manipulate objects without human intervention. Two key barriers are the complexity of current approaches, which require complicated hardware or precise perception to function effectively, and the challenge of understanding system performance in a tractable manner given the wide range of factors that impact successful grasping. This thesis presents sensors and simple control algorithms that relax the requirements on robot hardware, and a framework to understand the capabilities and limitations of grasping systems. / Engineering and Applied Sciences
| Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/12274286 |
| Date | 06 June 2014 |
| Creators | Jentoft, Leif Patrick |
| Contributors | Howe, Robert D. |
| Publisher | Harvard University |
| Source Sets | Harvard University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Rights | open |
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