A Robot Obstacle Avoidance Method Using Merged CNN Framework

Nai-Hsiang Chang, Yi-Hsing Chien, H. Chiang, Wei-Yen Wang, C. Hsu
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引用次数: 7

Abstract

In this paper, a merged convolution neural network (CNN) framework is proposed to automatically avoid obstacles. Although there are many methods for avoiding obstacles, previous methods mostly contain high energy-consuming and high cost. This paper aims to realize an image-based method with a monocular webcam. The experimental results illustrate that the proposed method can effectively avoid obstacles in mobile robot navigation.
基于合并CNN框架的机器人避障方法
本文提出了一种用于自动避障的合并卷积神经网络(CNN)框架。虽然避障方法很多,但以往的避障方法大多能耗高、成本高。本文旨在利用单目网络摄像头实现一种基于图像的方法。实验结果表明,该方法可以有效地避开移动机器人导航中的障碍物。
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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