Fig. 6. Motion of macro and micro mechanisms in the first experiment
Fig. 7. The tracking error of weld torch in the first experiment
Fig. 8. Motion of macro and micro mechanisms in the second experiment
Fig. 9. The tracking error of weld torch in the second experiment
6 Conclusions
In this paper, a welding robot was designed for large scaled workpieces. The two groups of macro and micro translational mechanisms provide large travel with high positioning precision for weld manipulation. The given welding trajectory can be grossly taught and planned in Cartesian space, and then the variables of the joints are planned in joint space via the inverse kinematics of the welding robot. The motion control of micro and macro joints is presented, by which the precision was compen- sated by the visual servo of micro joints based on feed back of visual sensing. The performance of seam tracking control of the welding robot is robust to the teaching trajectory in advance. Experimental results verified the effectiveness of the mechanisms of welding robot and the control system.
Acknowledgement
The authors would like to thank the National High Technology Research and Develop- ment Program of China for supporting this work under grant 2006AA04Z213. We would also like to thank China Postdoctoral Science Foundation (No. 20070410463) for their support.
References
1. Smith, T.F., Waterman, M.S.: Identification of Common Molecular Subsequences. J. Mol. Biol. 147, 195–197 (1981)
2. Bolmsjö, G., Olsson, M., Cederberg, P.: Robotic arc welding - trends and developments for higher autonomy. The Industrial Robot 29(2), 98–104 (2002)
3. Wang, Y., Tan, M., Jing, F., et al.: Kinematic analysis and application of a huge workpiece handling system based on multi-robot coordination. Robot 24(5), 451–455 (2002)
4. Lee, J., Kim, J., Kim, H., et al.: Development of multi-axis gantry type welding robot sys- tem using a PC-based controller. In: IEEE International Symposium on Industrial Electron- ics, 2001. Proceedings, vol. 3, pp. 1536–1541 (2001)
5. Ou, G., Zhang, H., Liu, G., et al.: Seam tracking control system of pedrailed intelligent arc welding robot. Robot 25(5), 448–451 (2003)
6. Bahrami-Samani, M., Agahi, M., Moosavian, S.A.A.: Design and analysis of a welding ro- bot. In: IEEE International Conference on Automation Science and Engineering, 2006, pp. 454–459 (2006)
7. Xu, H., Jia, P.: RTOC: A Rt-Linux based open robot controller. In: 2006 IEEE/RSJ Interna- tional Conference on Intelligent Robots and Systems, pp. 1644–1649 (2006)
8. Dai, W., Kampker, M.: PIN-a PC-based robot simulation and offline programming system using macro programming techniques. In: The 25th Annual Conference of the IEEE Indus- trial Electronics Society. Proceedings, vol. 1, pp. 29, 442–446 (1999)
Chapter 4
Intelligent Welding Robot Path Planning
Xue Wu Wang, Ying Pan Shi, Rui Yu and Xing Sheng Gu
Abstract Spot welding robots are now widely used in manufacturing industry, and usually many welding joints have to be traversed in welding process. The path planning for welding robot is based on engineering experiments where teaching and playback were applied in most cases. It usually takes the engineer much time to obtain desired welding path, and sometimes, it is difficult to find an optimal path for spot welding robot especially when the number of welding joints is huge. Hence, welding robot path planning has become one key technology in this field. Intelli- gent optimization algorithm is beneficial for realizing effective welding robot path planning. To this end, particle swarm optimization (PSO) algorithm was improved first. Then, the improved PSO algorithm was applied for path planning of welding robot, and the simulation results show the effectiveness of the method. 工件焊接机器人的设计英文文献和中文翻译(5):http://www.751com.cn/fanyi/lunwen_76074.html