飞行昆虫能够在复杂的自然环境中实现精确的导航，因此研究并借鉴飞行昆虫的导航机理，有助于开发更为高效的导航系统。飞行昆虫（以蜜蜂为代表）的视觉导航实验表明，飞行昆虫是基于图像信息流实现导航的。图像熵可以表征图像信息，为了更好地表征图像的纹理特征及空间分布，提出了对比度熵图的概念及其构造方法。借鉴光流算法及其应用于运动参数估计的思路，再结合卡尔曼滤波对结果进行优化，可得到对比度熵流仿生导航算法。实验表明，对比度熵图的导航算法比灰度熵图的导航算法有更好的导航性能。%With the facts that flying insects can achieve precise and high-speed navigation in complex natural environments,many experiments that focus on the navigation mechanism of flying insects have explored the possibilities for a more efficient,accurate and robust navigation strategy.In latest research results,it is revealed that honeybees navigate by images flowed through retinas. Concepts of entropy image and entropy flow are introduced to characterize topographic features and measure changes of the image respectively.A novel bionic visual navigation framework is proposed,integrating entropy flow with Kalman filter.To improve performance of intensity entropy image for characterizing texture feature and spatial distribution of an image,a functional concept of contrast entropy image is presented,which is applied to the proposed navigation algorithm.Comparing with simulation results of the normal intensity entropy image,a significant conclusion that contrast entropy image performs better and more robust in navigation has been made.
展开▼
