TeachBot : an automated, hands-on apprenticeship program

There are a plethora of medium and small-sized manufacturing companies that do not rely completely on autonomous systems. As a result, it is more economical to use a mixture of human labor and manufacturing robots; however, with the thousands of people who apply for these jobs, many do not have the experience to work along-side robots or understand how robots works. The research described by this thesis introduces a solution to this problem through TeachBot, an automated, hands-on apprenticeship program. TeachBot seeks to empower manufacturing workers with the skills necessary to work collaboratively with robots in the manufacturing industry. Through the use of ROS, the program teaches key topics in robotics such as encoders, kinematics, feedback, and programming through multiple interactive modules. TeachBot is setup with three main components: a JSON file of instructions, a JavaScript file, and a python file. The JavaScript file parses the instructions and sends commands to the python script. The python script then sends these commands to the robot. This process allows TeachBot to be modular and universal such that it can be modified easily and applied to any robot. This research focuses on implementing TeachBot onto the Sawyer Robot and the possible extension to the Universal Robot 5e.

Name thesis:degree_name

Bachelor

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

• Go, Albert(Albert P.)

Advisor dc:contributor.advisor

• Harry Asada.

• 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/1721.1/127921

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/127921