Robotic Welding, Intelligence and Automation (Lecture Notes in Control & Information Sciences)

Industrial Robot

ISSN: 0143-991x

Article publication date: 1 August 2005

175

Keywords

Citation

Mulligan, S. (2005), "Robotic Welding, Intelligence and Automation (Lecture Notes in Control & Information Sciences)", Industrial Robot, Vol. 32 No. 4. https://doi.org/10.1108/ir.2005.04932dae.001

Publisher

:

Emerald Group Publishing Limited

Copyright © 2005, Emerald Group Publishing Limited


Robotic Welding, Intelligence and Automation (Lecture Notes in Control & Information Sciences)

Springer-Verlag Berlin and Heidelberg GmbH & Co. K2004388 pp. (Paperback)3-540-20804-6£77.00http://www.springeronline.com/

Keywords: Robotics, Books, Welding, Automation

This book is mainly based on papers selected from the 2002 International Conference on Robotic Welding, Intelligence and Automation (RWIA 2002) held in Shanghai, China in December 2002. It contains 25 papers covering research in the fields of robotic welding, intelligent systems and automation.

Interesting welding developments include a modular concept for wire feeding with different welding processes (MIG, TIG, plasma, laser or hybrid laser-MIG) and a vision-based control system for TIG welding which uses simultaneous imaging of top and back face of the weld pool.

Several integrated systems for seam tracking are presented featuring laser scanning sensors, CCD cameras or a combination of both sensor types. Such systems were applied for TIG welding of titanium alloys and spiral submerged arc welded pipe.

The third section is devoted to intelligent robotic systems with an emphasis on control algorithms for legged and humanoid robots. Work on map building and localisation for autonomous mobile robots also features.

The final part of the book is largely theoretical and introduces some emerging intelligent techniques aimed at improving real-time operation, image compression and attribute reduction.

A common trend is towards integrating artificial neural network and fuzzy logic control methods. Neural networks are used for process modelling and selecting process parameters whilst fuzzy logic control is used to provide self-regulation or tuning of the response during operation.

The overall standard of the papers is high, but with a high mathematical content. Many of the papers go into detail on the image processing and control theories used, so this book would be of more interest to academics than engineers working in industry. The book is recommended for those with a background in control science rather than in applied robotic welding.

Stephen MulliganManufacturing Support and Arc Processes Group, TWI Limited

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