New bionic navigation algorithm based on the visual navigation mechanism of bees

Yufeng Huang, Yi Liu, Jianguo Liu
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Abstract

Through some research on visual navigation mechanisms of flying insects especially honeybees, a novel navigation algorithm integrating entropy flow with Kalman filter has been introduced in this paper. Concepts of entropy image and entropy flow are also introduced, which can characterize topographic features and measure changes of the image respectively. To characterize texture feature and spatial distribution of an image, a new concept of contrast entropy image has been presented in this paper. Applying the contrast entropy image to the navigation algorithm to test its’ performance of navigation and comparing with simulation results of intensity entropy image, a conclusion that contrast entropy image performs better and more robust in navigation has been made.
基于蜜蜂视觉导航机制的仿生导航新算法
通过对飞行昆虫尤其是蜜蜂视觉导航机理的研究,提出了一种将熵流与卡尔曼滤波相结合的导航算法。引入熵像和熵流的概念,分别表征地形特征和测量图像的变化。为了刻画图像的纹理特征和空间分布特征,本文提出了对比度熵图像的新概念。将对比度熵图像应用于导航算法中,对其导航性能进行了测试,并与强度熵图像的仿真结果进行了比较,得出了对比度熵图像在导航中的性能更好、鲁棒性更强的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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