Author ORCID Identifier
0000-0001-7669-0202
Defense Date
2024
Document Type
Thesis
Degree Name
Master of Science
Department
Mechanical and Nuclear Engineering
First Advisor
Dr. Ravi L. Hadimani
Abstract
Despite the incredible potential that collaborative robots have, they are underutilized in several industries that could benefit greatly. These specialized fields, such as additive manufacturing, face challenges that can be solved with the use of robotics, including advanced computer vision, end-effector tooling, and process refinement. My research aims to utilize collaborative robots in an effort to solve the above stated problems, for the specific fields of additive manufacturing. Specifically within this field is the automation of post-processing; this is normally completely manual, as the tools for automation are not sufficiently developed to handle the flexibility required for additive manufacturing. This is not only an issue with efficiency, it necessitates a dangerous environment, due to the health hazards such as fine metal powder. To address this, a vision system was implemented, specifically designed for ease of implementation, as it was developed without the use of machine learning, typically a requirement for segmenting 3D information. In this sense, this makes access to vision in collaborative robots more accessible for the purpose of workspace localization, as needing substantial training data to get precise results can serve as a barrier to adoption. This solution is shown to be 10 % more accurate and over 10 000 % faster when compared to the state-of-the-art for 3D vision without machine learning. Once a collaborative robot is sufficiently equipped with vision, one of the next barriers is access to versatile end-effector tooling. The highest temperature that commercial-off-the-shelf collaborative end effectors can withstand is around 300 ◦C; I developed an adaptable high temperature robotic gripper that can handle up to 1000 ◦C. It uses a casted ceramic insulator to take the heat, and 4140 alloy steel to dissipate whatever comes through. This end effector is one of a kind in terms of what it provides to collaborative robots, and serves to greatly enhance their utility, as it is inexpensive and be customized based on user needs. All of these milestones combine to push forward an upcoming field of study, collaborative robots, enabling sustainable processes and protecting the lives of humans.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
12-20-2024
Included in
Electrical and Computer Engineering Commons, Electro-Mechanical Systems Commons, Manufacturing Commons
