Model-Based Learning and Planning for Intelligent Manipulation Using Probabilistic Hybrid Models
While the rapid advancement of deep learning and grasp-affordance grasping has allowed the fast planning of grasping poses directly from visual inputs, it still commonly adopts an open-loop architecture that has made it slow to react and prone to failure, limiting its use in more complicated manipul...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/139602 |