Vision-based proprioception of a soft robotic finger with tactile sensing

Over the past decade, the development of soft robots has significantly progressed. Today, soft robots have a variety of usages in multiple fields, ranging from surgical robotics to prostheses to human-robot interaction. These robots are more versatile, adaptable, safe, robust, and dexterous than their conventional rigid-body counterparts. However, due to their high-dimensionality and flexibility, they still lack a quintessential human ability: the ability to accurately perceive themselves and the environment around them. To maximize their effectiveness, soft robots should be equipped with both proprioception and exteroception that can capture this intricate high-dimensionality. In this thesis, an embedded vision-based sensor, which can capture richly detailed information, is utilized to concurrently perceive proprioception and tactile sensing. Three proprioceptive methods are implemented: dot pose tracking, lookup table, and deep learning.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Liu, Sandra Q.

Advisor dc:contributor.advisor

• Edward H. Adelson.

• Mechanical Engineering.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/127131

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/127131