LAPSE:2024.1949
Published Article

LAPSE:2024.1949
ARM Cortex Simulation Design for Trajectory Curves Evaluation of Collaborative Robots’ Tungsten Inert Gas Welding
August 28, 2024
Abstract
An ARM Cortex simulation system for collaborative welding robots is presented in this paper. The components of the ARM Cortex SoC for embedded robot control, an OpenGL ES with image rendering, and a 3D geometry engine OpenCasCade for modeling are integrated for the purposes of simulating system self-controllability and cost effectiveness. This simulation of a collaborative welding robot achieved convenience while meeting the performance requirements; meanwhile, the auxiliary design was able to mark the trajectory of the robot’s end effector and reveal the collaborative robot’s inverse kinematic parameters, namely the position and Euler angle. An ARM Linux X11 Window environment that was set to create a 3D simulation rendering algorithm was built simultaneously. Then, the STEP model of the robot was loaded by using the OpenCasCade functionality. After that, the robot model and complex spline surface could be visualized by using the Qt QGLWidget. Finally, the correctness of the kinematic algorithm was verified by conducting simulations and analyzing the robot’s kinematics through the simulation results, which could verify the expected design and provide a set of fundamental samples for the robot trajectory industry regarding welding applications.
An ARM Cortex simulation system for collaborative welding robots is presented in this paper. The components of the ARM Cortex SoC for embedded robot control, an OpenGL ES with image rendering, and a 3D geometry engine OpenCasCade for modeling are integrated for the purposes of simulating system self-controllability and cost effectiveness. This simulation of a collaborative welding robot achieved convenience while meeting the performance requirements; meanwhile, the auxiliary design was able to mark the trajectory of the robot’s end effector and reveal the collaborative robot’s inverse kinematic parameters, namely the position and Euler angle. An ARM Linux X11 Window environment that was set to create a 3D simulation rendering algorithm was built simultaneously. Then, the STEP model of the robot was loaded by using the OpenCasCade functionality. After that, the robot model and complex spline surface could be visualized by using the Qt QGLWidget. Finally, the correctness of the kinematic algorithm was verified by conducting simulations and analyzing the robot’s kinematics through the simulation results, which could verify the expected design and provide a set of fundamental samples for the robot trajectory industry regarding welding applications.
Record ID
Keywords
ARM simulation system, AUBO robot welding, OCCT
Subject
Suggested Citation
Gao S, Geng H, Ge Y, Zhang W. ARM Cortex Simulation Design for Trajectory Curves Evaluation of Collaborative Robots’ Tungsten Inert Gas Welding. (2024). LAPSE:2024.1949
Author Affiliations
Gao S: School of Materials Science and Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan 030024, China
Geng H: School of Materials Science and Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan 030024, China
Ge Y: School of Materials Science and Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan 030024, China
Zhang W: School of Materials Science and Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan 030024, China
Geng H: School of Materials Science and Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan 030024, China
Ge Y: School of Materials Science and Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan 030024, China
Zhang W: School of Materials Science and Engineering, Taiyuan University of Science and Technology, 66 Waliu Road, Wanbailin District, Taiyuan 030024, China
Journal Name
Processes
Volume
12
Issue
6
First Page
1095
Year
2024
Publication Date
2024-05-27
ISSN
2227-9717
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Original Submission
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PII: pr12061095, Publication Type: Journal Article
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LAPSE:2024.1949
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https://doi.org/10.3390/pr12061095
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Aug 28, 2024
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