Award Date
5-1-2024
Degree Type
Thesis
Degree Name
Master of Science in Engineering (MSE)
Department
Mechanical Engineering
First Committee Member
Paul Oh
Second Committee Member
Kwang Kim
Third Committee Member
Woosoon Yim
Fourth Committee Member
Brendan Morris
Number of Pages
66
Abstract
A granular jamming gripper (GJG) is widely known as a Universal Gripper because of the wide range of objects that it can grasp and the simplicity of control, design, and manufacturing. Despite multitude of research improving the GJG, here, we focus on the base version of the GJG and attempt to glean the range of objects that it may reliably grasp. Despite the limited range of objects, which were a sphere, rectangular prism, and cylinder, we gleaned geometric properties as it relates to successful and unsuccessful grasping. This was based on the two types of testing: push and pull testing that measured the grasp ability, and grasp strength, respectively. The experiment results were surprising because we used the load cell in different orientations, but we attained the expected results as if the load cell was in the same orientation. These experiments attempt to validate and build upon current research by economically developing and testing the apparatus and gripper. From these experiments, we validated that the gripper grasp ability depends on the gripper diameter, and the contact angle with the object via introducing a “pressure” parameter that is the force by the surface area contact. Since a cartesian machine was used, we can nearly guarantee the depth into the object and therefore calculate the surface area contact using the 3D model.
Keywords
granular jamming; robotic gripper
Disciplines
Artificial Intelligence and Robotics | Mechanical Engineering | Robotics
File Format
File Size
2500 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Dowd, Jacob R., "Experiment Development and Validation of a Granular Jamming Robotic Gripper" (2024). UNLV Theses, Dissertations, Professional Papers, and Capstones. 4984.
http://dx.doi.org/10.34917/37650806
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
Included in
Artificial Intelligence and Robotics Commons, Mechanical Engineering Commons, Robotics Commons