 The proposed and colony algorithm addresses the limitations of traditional methods by incorporating fuzzy mathematics, optimizing probability selection and pheromone update formulas, and introducing a corner system mechanism for post-processing path optimization. Simulation results show that the improved algorithm has stronger path planning ability and higher efficiency, resulting in smoother paths with lower negative impact from environmental factors, providing a computational basis for effective multi-factor path planning in realistic environments. This article was authored by Mingchang Wang, Junyu Su, Feng Yang Wang, and others.