基于互信息的视觉伺服使用图像全局信息来实现伺服控制, 避免了对传统几何特征的提取、匹配和跟踪, 并且对光照变化、部分遮挡具有鲁棒性, 但由于其任务函数的高非线性, 该方法具有收敛域较小的缺点。提出了基于主成分分析(PCA)重建图像的互信息视觉伺服方法, 有效降低了任务函数的非线性。通过实验比较了基于PCA重建图像的互信息视觉伺服和基于原始图像的互信息视觉伺服收敛域大小及收敛速度, 并考虑了PCA中主成分个数的影响, 结果表明基于PCA重建图像的互信息视觉伺服有效地扩大了互信息视觉伺服的收敛域, 且具有更快的收敛速度。

The mutual information based visual servo uses the global information of the image to realize servo control, which avoids the extraction, matching and tracking of traditional geometric features, and is robust to light changes and partial occlusion. However, due to the high nonlinearity of its cost function, this method has the disadvantage of small convergence region. A mutual information visual servo method based on principal component analysis (PCA) for dimension-reduced image reconstruction is proposed, which effectively decreases the nonlinearity of the cost function. The convergence region size and convergence speed of mutual information visual servo based on PCA reconstructed image and original image were compared through experiments, and the influence of the number of principal components in PCA is considered. The results show that the mutual information visual servo based on PCA reconstruction image effectively expands the convergence region of mutual information visual servo and has faster convergence speed.