Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-11T10:36:21.833Z Has data issue: false hasContentIssue false
  • English
  • Français

A lead through approach for programming a welding arm robot using machine vision

Published online by Cambridge University Press:  04 June 2021

Mohamed Hosni Mohamed Ali Open the ORCID record for Mohamed Hosni Mohamed Ali [Opens in a new window]  and
Mostafa Rostom Atia
Mohamed Hosni Mohamed Ali*
Affiliation:
Arab Academy for Science, Technology and Maritime Transport, Sheraton, Cairo, Egypt
Mostafa Rostom Atia
Affiliation:
Arab Academy for Science, Technology and Maritime Transport, Sheraton, Cairo, Egypt
*
*Corresponding author. Email: m-hosni@hotmail.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Welding is a complex manufacturing process. Its quality depends on the welder skills, especially in welding complex paths. For consistency in modern industries, the arm robot is used to accomplish this task. However, its programming and reprogramming are time consuming and costly and need an expert programmer. These limit the use of robots in medium and small industries. This paper introduces a new supervised learning technique for programming a 4-degree of freedom (DOF) welding arm robot with an automatic feeding electrode. This technique is based on grasping the welding path control points and motion behavior of an expert welder. This is achieved by letting the welder move the robot end effector, which represents the welding torch, through the welding path. At the path control points, the position and speed are recorded using a vision system. Later, these data are retrieved by the robot to replicate the welding path. Several 2D paths are tested to assess the proposed approach accuracy and programming time and easiness in comparison with the common one. The results prove that the proposed approach includes fewer steps and consumes less programming time. Moreover, programming can be accomplished by the welder and no need for an expert programmer. These enhancements will improve the share of robots in welding and similar industries.

Keywords

lead through programmingwelding robotmachine vision
Type
Article
Information
Robotica , Volume 40 , Issue 3 , March 2022 , pp. 464 - 474
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Wenming, Z., Zhihai, D. and Zhanqi, L., “Present Situation and Development Trend of Welding Robot,” 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE) (2017).Google Scholar
Wei, M. H. A. L. and Yong, L. S., “An Industrial Application of Control of Dynamic Behavior of Robots - A Walk Through Programmed Welding Robot,” Proceedings of the IEEE, International Conference on Robotics and Automation, San Francisco (2000).Google Scholar
Lin, H.-C., Fan, Y., Tang, T. and Tomizuka, M., “Human Guidance Programming on a 6-DoF Robot with Collision Avoidance,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea (2016).Google Scholar
Karlsson, M., Robertsson, A. and Johansson, R., “Autonomous Interpretation of Demonstrations for Modification of Dynamical Movement Primitives,” IEEE International Conference on Robotics and Automation (ICRA), Singapore (2017).Google Scholar
Bascetta, L., Ferretti, G., Magnani, G. and Rocco, P., “Walk-through programming for robotic manipulators based on admittance control,” Robotica 31(7), 1143–1153 (2013).CrossRefGoogle Scholar
Qi, L., Zhang, D. and Li, J., “A Lead-Through Robot Programming Approach Using A 6-DOF Wire-based Motion Tracking Device,” Proceedings of the 2009 IEEE, International Conference on Robotics and Biomimetics, Guilin, China (2009).CrossRefGoogle Scholar
Kim, T.-W., Lee, K.-Y., Kim, J., Oh, M.-J. and Lee, J. H., “Wireless Teaching Pendant for Mobile Welding Robot in Shipyard,” Proceedings of the 17th World Congress, The International Federation of Automatic Control, Seoul, Korea (2008).CrossRefGoogle Scholar
Muzan, I. W., Faisal, T., Al-Assadi, H. and Iwan, M., “Implementation of Industrial Robot for Painting Applications,” International Symposium on Robotics and Intelligent Sensors (IRIS) (2012).CrossRefGoogle Scholar
Lin, H.-C., Tang, T., Fan, Y., Zhao, Y., Tomizuka, M. and Chen, W., “Robot Learning from Human Demonstration with Remote Lead Through Teaching,” European Control Conference (ECC) (2016) pp. 388–394.Google Scholar
Mohammed, A. A. and Sunar, M., “Kinematics Modeling of a 4-DOF Robotic Arm,” International Conference on Control, Automation and Robotics, Singapore (2015).CrossRefGoogle Scholar
Somasundar, A. and Yedukondalu, G., “Robotic Path Planning and Simulation by Jacobian Inverse for Indstrial Applications,” International Conference on Robotics and Smart Manufacturing (RoSMa) (2018).CrossRefGoogle Scholar
Ferreira, L. A., Figueira, Y. L., Iglesias, I. F. and Souto, M. Á., “Offline CAD-based Robot Programming and Welding Parametrization of a Flexible and Adaptive Robotic Cell Using Enriched CAD/CAM System for Shipbuilding,” 27th International Conference on Flexible Automation and Intelligent Manufacturing, Modena, Italy (2017).CrossRefGoogle Scholar
Lin, H.-I., Liu, Y.-C. and Lin, Y.-H., “Intuitive kinematic control of a robot arm via human motion,” Procedia Eng. 79, 411–416 (2014). https://www.sciencedirect.com/science/article/pii/S1877705814009412.CrossRefGoogle Scholar
Lachat, E., Macher, H., Mittet, M. A., Landes, T. and Grussenmeyer, P., “First Experiences with Kinect v2 Sensor for Close Range 3D Modeling,” 6th International Workshop 3D-ARCH, Avila, Spain (2015).10.5194/isprsarchives-XL-5-W4-93-2015CrossRefGoogle Scholar
Prashanth, B. and A. R. S, “Design, Fabrication and Control of Four Degrees of Freedom Serial Manipulator,” International Conference on Smart Systems and Inventive Technology (ICSSIT) (2018).Google Scholar
Corke, P., “Using the Robotics Toolbox with a real robot,” In: Robotics, Vision & Control (Springer, 2013).Google Scholar