针对复杂干扰环境下智能移动机器人自主导航问题，为了实现低成本、高精度、强鲁棒性、完全自主的导航，提出了一种偏振光/双目视觉仿生组合导航方法。首先，设计了图优化紧耦合的组合算法，推导优化函数并将偏振定向传感器/双目视觉传感器的数据融合，然后，搭建仿生偏振定向传感器/双目视觉传感器仿生组合导航实验平台，最后，通过室外汽车搭载实验对该仿生组合导航系统的性能进行了测试，并与传统视觉算法进行了比较。结果显示：航向角精度较传统视觉算法提高了38.9%，位置精度提高了8.9%。该组合导航系统可以减小传统视觉算法航向角误差、提高鲁棒性，而且使用仿生偏振定向传感器实时性好、抗干扰能力强，可以满足室外地面载体导航时的精度和可靠性要求，同时该组合导航系统使用两种仿生导航方式，更加接近生物导航机理。

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.