Laser plate cutting not only improves production efficiency, but is also easier to adapt to changing production needs. At present, laser cutting has been widely used in automobile part cutting. However, single laser cutting is the most widely used in both theoretical research and practical production. However, in large-scale industrial production, this cutting method cannot meet the production needs. To further improve the cutting efficiency of automobile parts, dual laser collaborative cutting path planning was studied. First, the mathematical model of double laser collaborative cutting was established. Second, a fuzzy clustering vaccine immune algorithm was proposed to plan the double laser cutting path. Finally, the irregular polygon samples provided by the ESICUP website and actual automobile part data were selected for algorithm simulation verification. Experimental results show that compared with the traditional GA/IA algorithm for single laser cutting path planning, the laser cutting path planned by the proposed algorithm has a shorter empty travel and higher stability.