A bionic integrated navigation method of polarized light/binocular vision is proposed to realize the low-cost， high-precision， strong robustness and completely autonomous navigation for intelligent mobile robot under complicated disturbing environment. Firstly， based on graph-based optimization， a tightly-coupled navigation algorithm is designed. By constructing the optimization function， the data of polarization sensor and binocular vision sensor are fused. Then， the experimental platform of the bionic integrated navigation method is built. Finally， the performance of the bionic integrated navigation method is tested through the outdoor vehicle carrying experiment， and compared with the traditional vision algorithm. The results show that the heading angle accuracy is improved by 38.9% and the position accuracy is improved by 8.9% compared with the traditional vision algorithm. The proposed method can reduce the heading angle error of vision algorithm and improve the robustness. Moreover， the bionic polarization sensor has the advantages of good real-time performance and strong anti-interference ability， which can meet the accuracy and reliability requirements of outdoor ground carrier navigation. The proposed method uses two kinds of bionic navigation methods， which make comprehensive use of the advantages of biological navigation.