Welding robots have a wide range of applications in manufacturing industries. There are usually many welded joints in the welding task, and a reasonable welding path passes through these welded joints has a significant impact on the welding efficiency. Traditional manual path planning techniques can handle a small number of welded joints effectively, but when the number of welded joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Genetic algorithmparticle swarm optimization (GA-PSO) is based on the advantages of genetic algorithm (GA) and particle swarm optimization (PSO) to solve the welding robot path planning problem. The simulation results indicate that the algorithm has strong searching ability and practicality and is suitable for welding robot path planning.