Robot intelligent welding programming based on line structure light sensing

The traditional robot automatic welding programming method relies heavily on the accuracy of CAD model for welding workpiece, so its application is limited for small batch, irregular and multiple type welding tasks. In this paper, with the traditional welding programming software, a new three-dimensional sensing and point cloud modeling approach of the weld is constructed by introducing a line structure light sensor, thus the accurate extracting of weld seams is realized. A general intelligent welding programming method and software system is developed by using the framework of the combination of front-end perception, point cloud processing, and back-end off-line programming. Through modular design, a unified interface is designed for the whole process of welding, from welding seam extraction to robot welding intelligent programming, is realized for different types of sensors, robots and scanning methods. The experimental results showed that the proposed robot intelligent welding programming system is effective, universal and extensible.

[1]  Henrik Gordon Petersen,et al.  From the Guest Editors - Industrial robotics applications and industry-academia cooperation in Europe , 2005, IEEE Robotics Autom. Mag..

[2]  Nuno Mendes,et al.  CAD-based robot programming: The role of Fuzzy-PI force control in unstructured environments , 2010, 2010 IEEE International Conference on Automation Science and Engineering.

[3]  Huang Jin,et al.  3D scanning system for digital dental based on line structured light sensor , 2012, 2012 International Conference on System Science and Engineering (ICSSE).

[4]  Philips S. Ogun,et al.  Feature extraction and tracking of a weld joint for adaptive robotic welding , 2014, 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV).

[5]  I-Ming Chen,et al.  Automatic robot taping: system integration , 2015, 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[6]  Shi Jian-feng,et al.  Research on phased array ultrasonic technique for testing butt fusion joint in polyethylene pipe , 2016, 2016 IEEE Far East NDT New Technology & Application Forum (FENDT).

[7]  Silvia Silva da Costa Botelho,et al.  Seam tracking and welding bead geometry analysis for autonomous welding robot , 2017, 2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR).

[8]  Guanglin Li,et al.  Development of Sensory-Motor Fusion-Based Manipulation and Grasping Control for a Robotic Hand-Eye System , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[9]  Quan Pan,et al.  Random sample consensus algorithm for multiple target tracking in over-the-horizon radar , 2017, 2017 18th International Radar Symposium (IRS).

[10]  Peter Korondi,et al.  Robotized multi-pass Tungsten Inner Gas welding of Francis hydro power turbines , 2017, 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE).

[11]  Jie Bai,et al.  The mobile robot path planning with motion constraints based on Bug algorithm , 2017, 2017 Chinese Automation Congress (CAC).