Robot Localization in RGB-D Images Using PCA and CNN

Alwaled Khalid Taha, G. Cansever
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Abstract

Human beings have always used the resources at their disposal as tools to help carry out tasks in the most effective, fast and safe way. As technology advances, these tools are being used in increasingly complex machinery capable of performing complicated jobs precisely and often better than a human could have in this paper we aim at performing a robust robot localization by reducing the 3d images into 2d images using PCA algorithm and using CNN for feature extraction and classification of the images.
基于PCA和CNN的RGB-D图像机器人定位
人类一直把自己掌握的资源作为工具,以最有效、最快速、最安全的方式完成任务。随着技术的进步,这些工具正被用于越来越复杂的机器中,这些机器能够精确地执行复杂的工作,而且往往比人类做得更好。在本文中,我们的目标是通过使用PCA算法将3d图像减少到2d图像,并使用CNN对图像进行特征提取和分类,从而实现强大的机器人定位。
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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