Wu C., Wu S., Kim J., Magluyan D., Kawamoto-Kindred D., Zhou Y.H., Cao N., Zhao H., Kuang Z., Kidd T., Wu C., Wu S., Dobbs S.
California State Polytechnic University, Pomona, US
Keywords: forward kinematics, graphene sheet, inverse kinematics, machine learning, robotic arm, supercapacitor
Robotics is a field that seeks to use more precise and accurate mechanical manipulation to improve the speed, efficiency, and safety of certain tasks where human actions would be more of a liability than a benefit. The method is to take a currently existing robotic arm, which can successfully move and place objects for the goal of assembling a supercapacitor, and add implementations that would further automate and improve the efficiency of the process [1-2]. One desire is to have the robot run on a standalone computer (Jetson TX2) instead of utilizing one’s personal computer of a group member. This would move the project approach towards full automation and separation from human operation. Another desire is to incorporate the OpenCR1.0 development board (from ROBOTIS Inc.) for the purpose of handling inverse kinematics calculations and controlling other pieces of hardware. Currently, the system still uses hardcoded forward kinematics for some aspects of the arm’s movement, which adds additional complexity and difficulty in troubleshooting to the project. The final goal is to modify the arm’s end-effector so that it can not only pick up and transport the supercapacitor components, but also dispense electrolyte gel in- between parts [3]. The overall goal is to increase separation from human operation of the project so that it can increase its efficiency and efficacy.
Journal: TechConnect Briefs
Volume: TechConnect Briefs 2021
Published: October 18, 2021
Pages: 122 - 125
Industry sectors: Advanced Materials & Manufacturing | Medical & Biotech
Topics: Advanced Manufacturing, Materials Characterization & Imaging
ISBN: 978-0-578-99550-2