Gelsight robotic fingertip

Tactile sensing is integral in robotic manipulation, enabling robot hands to identify objects and explore the environment. The gelsight tactile sensor designed in MIT CSAIL is able to reconstruct the surface topography of objects up to submicron accuracy. This thesis is focused on the integration of the gelsight tactile sensor into the MIT Team's gripper for the 2017 Amazon Robotics Challenge. The design of the sensor is dependent on the three manipulation primitives in the gripper platform: scooping, grasping, and suction. This paper discusses the primitives and the sensory inputs they would require to create more precise manipulation models. We then propose a gelsight tactile sensor around those primitives, creating a design that can recover shear, deflection, compliance, and contact area information. Lastly, we implement some of the image processing to recover deflection by creating a mapping between image points and ground truth vicon values, producing an 75% accuracy rate within a distance threshold, a value that can be improved with increased measurements and better image processing techniques. Further work focuses on image processing for shear, compliance, and contact area, to be integrated into the overall design for the 2017 ARC gripper.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Liu, Melody Grace

Advisor dc:contributor.advisor

• Alberto Rodriguez.

• Mechanical Engineering.

Statement dc:rights

• 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.

Licence dc:rights.uri

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

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/113503

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/113503