A study of welding robot path planning application based on Genetic Ant Colony Hybrid Algorithm

In this paper, the genetic algorithm is added to each iteration of the ant colony system, taking the and advantage of fast convergence of the genetic algorithm to speed up the convergence rate of the ant colony system. While the mutation mechanism of genetic algorithm helps ant colony system improve its ability to jump out of the local optimization. Thus, a hybrid algorithm with the advantages of genetic algorithm and ant colony algorithm is formed. The application of this method in welding robot path planning is realized by modeling, we compare the optimal solution and convergence speed of genetic ant colony hybrid algorithm with genetic algorithm in path planning, and the comparison results show that the hybrid algorithm is superior to genetic algorithm. Simulation results show that this hybrid algorithm solves the contradiction between the convergence speed and the optimization degree of welding robot path planning, and has good application in the welding robot path planning.