Robotic Welding, Intelligence and Automation

1. Front Matter

   Pages I-XII

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2. General Intelligent Robotics

   1. Behavior-Based Intelligent Robotic Technologies in Industrial Applications

      • Z. X. Gan, H. Zhang, J. J. Wang

      Pages 1-12

   2. Detecting System Modeling and Hand-Eye Calibration for a Robot to Detect the Ablation of Hydro-turbine Blades

      • Wang Shenghua, Du Dong, Zhang Wenzeng, Chang Baohua, Chen Qiang

      Pages 13-20

   3. Dynamic Model and Control for an Omnidirectional Mobile Manipulator

      • Dong Xu, Dongbin Zhao, Jianqiang Yi

      Pages 21-30

   4. Soft Touch Control Strategy of Remote Teaching Based on Force Sensing

      • L. J. Liu, H. M. Gao, G. J. Zhang, L. Wu

      Pages 31-39

   5. A Novel Pose Estimation System for Indoor Mobile Robots Based on Two Optical Sensors

      • Xiang-min Tan, Dongbin Zhao, Jianqiang Yi

      Pages 41-49

   6. Haptic Teleoperation of Robotic Manipulator

      • Wusheng Chou, Jing Xiao

      Pages 51-59

   7. Practical Stabilization of Nonholonomic Mobile Robots Moving on Uneven Surface

      • Xiaocai Zhu, Guohua Dong, Dewen Hu

      Pages 61-70

   8. An Efficient Method for Collision Detection and Distance Queries in a Robotic Bridge Maintenance System

      • J. Xu, D. K. Liu, G. Fang

      Pages 71-82

   9. Laser Vision System Based on Synchronized Scanning Method

      • Victor S. Cheng, L. J. Hao, X. Z. Chen, S. Zhang, Y. Z. Chen

      Pages 83-89

   10. An Object Oriented Robot Programming Approach in Robot Served Plastic Injection Molding Application

       • J. G. Ge, X. G. Yin

       Pages 91-97

   11. A Wide Angle-of-View Thermal Imaging System Utilizing the Rotation of Optical Path

       • Victor S. Cheng, Su Zhang, Xue-Song Lu, Xi-Zhang Chen, Ya-Zhu Chen

       Pages 99-104

3. Intelligent Techniques for Robotic Welding

   1. On the Key Technologies of Intelligentized Welding Robot

      • S. B. Chen

      Pages 105-115

   2. Computer Simulation of Neural Network Control System for CO2 Welding Process

      • Fan Ding, Shi Yu, Li Jianjun, Ma Yuezhou, Chen Jianhong

      Pages 117-125

   3. Numerical Study of Tube Cathode Arc with Anode Melting

      • S. Tashiro, M. Tanaka

      Pages 127-134

   4. Numerical Simulation of Molten Droplet Shape and Electromagnetic Pinch Effect in Short-Circuit CO2 Welding

      • Z. M. Zhu, W. K. Wu, Q. Chen

      Pages 135-144

   5. Planning the Torch Orientation of Planar Lap Joint in Robotic Welding

      • L. Zhou, J. F. Wang, T. Lin, S. B. Chen

      Pages 145-151

   6. Automatic Path Planning for Welding Robot Based on Reconstructed Surface Model

      • Wusheng Chou, Liang You, Tianmiao Wang

      Pages 153-161

   7. Study on the Control Strategy of Commutation Process in Variable Polarity Plasma Arc Welding

      • Li Zhining, Du Dong, Wang Li, Chang Baohua, Zhang Hua

      Pages 163-170

   8. Recognition of Macroscopic Seam for Complex Robotic Welding Environment

      • X. Z. Chen, S. B. Chen, T. Lin

      Pages 171-178

Robotic welding systems have been used in different types of manufacturing. They can provide several benefits in welding applications. The most prominent advantages of robotic welding are precision and productivity. Another benefit is that labor costs can be reduced. Robotic welding also reduces risk by moving the human welder/operator away from hazardous fumes and molten metal close to the welding arc. The robotic welding system usually involves measuring and identifying the component to be welded, we- ing it in position, controlling the welding parameters and documenting the produced welds. However, traditional robotic welding systems rely heavily upon human interv- tion. It does not seem that the traditional robotic welding techniques by themselves can cope well with uncertainties in the welding surroundings and conditions, e. g. variation of weld pool dynamics, fluxion, solid, weld torch, and etc. On the other hand, the advent of intelligent techniques provides us with a powerful tool for solving demanding re- world problems with uncertain and unpredictable environments. Therefore, it is intere- ing to gather current trends and to provide a high quality forum for engineers and researchers working in the filed of intelligent techniques for robotic welding systems. This volume brings together a broad range of invited and contributed papers that describe recent progress in this field.

• Advanced Welding Robots
• Methodologies for Welding Process
• Robotic Welding
• Seam Tracking
• Tracking
• Trend
• Welding Robot
• automation
• computer vision
• control
• intelligent control
• robot
• robotics
• sensing
• system

• Washington University, St. Louis, USA

  Tzyh-Jong Tarn

• Institute of Welding Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China

  Shan-Ben Chen

• Advanced Robotics and Intelligent Control Centre (ARICC), School of Electrical and Electronic Engineering, Singapore Polytechnic, Singapore, Singapore

  Changjiu Zhou

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