More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch

More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch

For humans, the process of grasping an object relies heavily on rich tactile feedback. Most recent robotic grasping work, however, has been based only on visual input, and thus cannot easily benefit from feedback after initiating contact. In this letter, we investigate how a robot can learn to use t...

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Bibliographic Details
Main Authors: Calandra, Roberto (Author), Owens, Andrew (Author), Jayaraman, Dinesh (Author), Lin, Justin (Author), Yuan, Wenzhen (Author), Malik, Jitendra (Author), Adelson, Edward H (Author), Levine, Sergey (Author)
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: Institute of Electrical and Electronics Engineers (IEEE), 2020-08-25T19:21:29Z.
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