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.

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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.