Force Feedback and Tactile Sensing for Robotic Teleoperation of Contact Rich Manipulation Tasks

Imitation learning has shown promising results in teaching robots new skills. We propose augmenting the ALOHA bimanual teleoperation system with haptic feedback to obtain higher quality expert demonstrations. We add two types of haptic feedback: force feedback and cutaneous feedback in both a real and simulation teleoperation system. Additionally, we propose to add tactile sensors to observe the impact of tactile data to imitation learning models in solving fine manipulation tasks.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Karpoor, Shreya S.

Advisor dc:contributor.advisor

• Agrawal, Pulkit

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/156561

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/156561