随机噪声平板下光学复眼内外参联合标定

Joint Internal and External Parameters Calibration of Optical Compound Eye Based on Random Noise Calibration Pattern

光学复眼在无人系统的精确定位制导、避障导航等任务中得到了越来越广泛的应用,其中光学复眼的高精度标定是保障上述任务质量的前提。通常经典的张氏棋盘格标定法要求光学复眼的每个子眼都必须观测到完整的棋盘格,然而,由于光学复眼结构的复杂性,在实际标定过程中难以满足这一要求。为解决张氏标定法的局限性,该文提出一种基于随机噪声平板的光学复眼内外参联合标定算法,该算法通过子眼拍摄随机噪声平板的局部信息,可简单快速地实现任意构型和子眼数量的光学复眼内外参联合标定。为了提高光学复眼标定的稳定性,设置多阈值匹配机制解决子眼视场特征点数量稀疏导致图像匹配失效的问题。同时,给出了光学复眼内外参联合标定的误差模型,用来衡量所提出算法的精确度。在与张氏棋盘格标定法进行实验对比中,验证所提算法的稳定性和鲁棒性,并在光学复眼实物系统中,验证了所提联合标定算法具有较高的精度。

In tasks such as precise guidance and obstacle avoidance navigation based on optical compound eyes,the calibration of optical compound eyes plays a crucial role in achieving high accuracy.The classical Zhang’s calibration method requires each ommatidium of the optical compound eyes to observe a complete chessboard pattern.However,the complexity of the optical compound eye structure makes it difficult to satisfy this requirement in practical applications.In this paper,a joint internal and external parameters calibration algorithm of optical compound eyes based on a random noise plate calibration pattern is proposed.This algorithm utilizes the local information captured by the ommatidia when photographing the random noise calibration pattern,enabling simple and fast calibration for optical compound eyes with arbitrary configurations and numbers of ommatidia.To improve the robustness of the calibration,a multi-threshold matching mechanism is introduced to address the issue of sparse feature point quantity in ommatidial visual fields leading to matching failures.Moreover,an error model for the joint internal and external parameters calibration of optical compound eyes is presented to evaluate the accuracy of the proposed algorithm.Experimental comparisons with Zhang’s calibration method demonstrate the robustness of the proposed algorithm.Furthermore,the high accuracy of the proposed joint calibration algorithm is validated in a physical system of optical compound eyes.