High-resolution tactile sensing for robotic perception

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.

Bibliographic Details
Main Author: Yuan, Wenzhen. Ph. D. Massachusetts Institute of Technology
Other Authors: Edward H. Adelson and Mandayam A. Srinivasan.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2019
Subjects:
Online Access:http://hdl.handle.net/1721.1/120267
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author Yuan, Wenzhen. Ph. D. Massachusetts Institute of Technology
author2 Edward H. Adelson and Mandayam A. Srinivasan.
author_facet Edward H. Adelson and Mandayam A. Srinivasan.
Yuan, Wenzhen. Ph. D. Massachusetts Institute of Technology
author_sort Yuan, Wenzhen. Ph. D. Massachusetts Institute of Technology
collection MIT
description Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
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spelling mit-1721.1/1202672019-04-10T14:03:29Z High-resolution tactile sensing for robotic perception Yuan, Wenzhen. Ph. D. Massachusetts Institute of Technology Edward H. Adelson and Mandayam A. Srinivasan. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 107-113). Why is it so difficult for the present-day robots to act intelligently in the real-world environment? A major challenge lies in the lack of adequate tactile sensing technologies. Robots need tactile sensing to understand the physical environment, and detect the contact states during manipulation. A recently developed high-resolution tactile sensor, GelSight, which measures detailed information about the geometry and traction field on the contact surface, shows substantial potential for extending the application of tactile sensing in robotics. The major questions are: (1) What physical information is available from the high-resolution sensor? (2) How can the robot interpret and use this information? This thesis aims at addressing the two questions above. On the one hand, the tactile feedback helps robots to interact better with the environment, i.e., perform better exploration and manipulation. I investigate various techniques for detecting incipient slip and full slip during contact with objects, which helps a robot to grasp them securely. On the other hand, tactile sensing also helps a robot to better understand the physical environment. That can be reflected in estimating the material properties of the surrounding objects. I will present my work on using tactile sensing to estimate the hardness of arbitrary objects, and making a robot autonomously explore the comprehensive properties of common clothing. I also show our work on the unsupervised exploration of latent properties of fabrics through cross-modal learning with vision and touch. by Wenzhen Yuan. Ph. D. 2019-02-05T16:02:29Z 2019-02-05T16:02:29Z 2018 2018 Thesis http://hdl.handle.net/1721.1/120267 1083220155 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 113 pages application/pdf Massachusetts Institute of Technology
spellingShingle Mechanical Engineering.
Yuan, Wenzhen. Ph. D. Massachusetts Institute of Technology
High-resolution tactile sensing for robotic perception
title High-resolution tactile sensing for robotic perception
title_full High-resolution tactile sensing for robotic perception
title_fullStr High-resolution tactile sensing for robotic perception
title_full_unstemmed High-resolution tactile sensing for robotic perception
title_short High-resolution tactile sensing for robotic perception
title_sort high resolution tactile sensing for robotic perception
topic Mechanical Engineering.
url http://hdl.handle.net/1721.1/120267
work_keys_str_mv AT yuanwenzhenphdmassachusettsinstituteoftechnology highresolutiontactilesensingforroboticperception