ROS 2 configuration for delta robot arm kinematic motion and stereo camera visualization

The Delta robot is one of the robot types that is used in agriculture and industrial application. However, before the complex physical development of the robot, a simulation needs to be developed to ensure the perfect functionality of the design. Therefore, this paper presented a development of simu...

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Bibliographic Details
Main Authors: Mohd Saad, Wira Hidayat, Saipullah, Khairul Muzzammil, Chong, Sook Hui, Idris, Muhammad Idzdihar, Ahmad Radzi, Syafeeza
Format: Article
Language:English
Published: Universitas Muhammadiyah Yogyakarta 2022
Online Access:http://eprints.utem.edu.my/id/eprint/26629/2/ROS%202%20CONFIGURATION%20FOR%20DELTA%20ROBOT%20ARM%20KINEMATIC%20MOTION%20AND%20STEREO%20CAMERA%20VISUALIZATION.PDF
http://eprints.utem.edu.my/id/eprint/26629/
https://journal.umy.ac.id/index.php/jrc/article/view/14436/7376
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Summary:The Delta robot is one of the robot types that is used in agriculture and industrial application. However, before the complex physical development of the robot, a simulation needs to be developed to ensure the perfect functionality of the design. Therefore, this paper presented a development of simulation for a parallel delta robot using a Robot Operating System 2 (ROS 2) environment and stereo camera visualization. The contribution of this research is to present the development details and the proposed solution to solve issues encountered during the development. The development of script in the format of eXtensible Markup Language (XML), Unified Robot Description Format (URDF), and Simulation Description Format (SDF) are presented for describing a robot's physical structure, allowing a robotic system to be depicted in a tree structure, and defining the delta robot arm, which is made up of closed-loop kinematic chain linkage that will be simulated in Gazebo. For the results, several Gazebo plugin libraries are compared and tested for the wheels motion control, stereo camera visualization, and delta robot arm kinematic motion. From the experiment, the best method is inverse kinematic motion the method is selected and used in the simulation. The selected method resulted in an average percentage error of 3.92%, 3.72%, and 2.92%, respectively for each joint.