Forward and optimised IK utilising the Levenberg-Marquardt algorithm 6-DOF robot manipulator for sorting applications
Mohammad Hafidz Hasnor Faiz, Norashikin M. Thamrin, Megat Syahirul Amin Megat Ali, Idris Zainal Abidin
Abstract
Colour sorting robots automate industries, but translating image data to robot movement is expensive and complicated. Vision sensors require a lot of processing power, which can slow down and strain the robot. Real-time colour sorting hardware and software integration complicates things. This work uses robotic operating system (ROS) to solve vision-guided colour sorting problems in Cartesian space. Ubuntu 20.04, ROS Noetic, a Raspberry Pi, a camera, and six servos. In Jupyter Lab, unified robotic description format (URDF) is used to build a virtual kinematic model, and Levenberg-Marquardt (LM) optimisation guides object manipulation. OpenCV image processing uses colour conversion, Canny edges, and midpoint estimation to detect coloured objects efficiently. The average servo movement error is 0.46 degrees, and the robot manipulator's final destination positioning error is 1.65 mm. The average object edge detection error is 0.33 mm, and the red, green, blue (RGB) colour distance is 57.84. ROS-based robot manipulator achieves impressive Cartesian space colour sorting accuracy despite image processing challenges, enabling real-world deployment.
Keywords
Edge detection; Forward kinematics; Image processing; Inverse kinematics; Levenberg-Marquardt; Robot manipulator; Robot operating system
DOI:
https://doi.org/10.11591/eei.v14i2.8723
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Bulletin of EEI Stats
Bulletin of Electrical Engineering and Informatics (BEEI) ISSN: 2089-3191, e-ISSN: 2302-9285 This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU) .