自主机器人导航中避碰障碍学习研究

Á. Sánchez-García, H. Rios-Figueroa, Xavier Limon-Riaño, J. Sanchez-Garcia, K. Cortés-Verdín
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引用次数: 0

摘要

避障是机器人导航的主要任务之一。提出了一种基于单目视觉的机器人导航方法。因此,通过估计接触时间来避免碰撞,需要对障碍物进行精确的分割。我们在这个研究过程中的建议是基于使用YOLO,通过一个训练过程,机器人识别图像的哪些区域是潜在的障碍。实验是在一个真实的环境中进行的,日光不足,没有控制照明参数。这种方法的初步结果是令人满意的,尽管该项目将在了解其他障碍的情况下继续进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Learning Obstacles to Avoid Collisions in Autonomous Robot Navigation
Avoiding obstacles is one of the main tasks in robotic navigation. In this paper, robot navigation using monocular vision is presented. Therefore, an accuracy in the segmentation of obstacles is necessary to avoid collisions by estimating the Time-to-Contact. Our proposal in this research process is based on using YOLO so that through a training process, the robot identifies which regions of the image are potentially obstacles. The experimentation was performed in a real environment, with low daylight and without controlling lighting parameters. The first results of this approach are satisfactory although this project will continue with the learning of other obstacles.
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