Abstract
For spot welding task, reasonable welding path is useful for welding efficiency improvement. Obstacle avoidance is essential for safe welding, and energy consumption is another factor needed to be considered in the process of welding robot path planning. The shortest path length and energy consumption are considered as optimization objectives, and obstacle avoidance is set as the constraint condition in this article. After analysis of geometric obstacle avoidance strategy, energy consumption, and robot path length, the multi-objective welding path optimization model is given first. Then, the clustering guidance multi-objective particle swarm algorithm (CG-MOPSO) is presented. At last, the improved algorithm is applied to realize the welding robot path optimization, and the algorithm effectiveness is verified through the Pareto optimal solution.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
