Path recognition for outdoor navigation using artificial neural networks: Case study

P. Shinzato, L. C. Fernandes, F. Osório, D. Wolf
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引用次数: 10

Abstract

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community. In order to execute a safe navigation on outdoors it is necessary to identify parts of the terrain that can be traversed by the robot and parts that should be avoided. This paper describes an analyses of an image-based terrain identification based on different visual information using a multi-layer perceptron neural network. Experimental tests using an outdoor robot and a video camera have been conducted in real scenarios to evaluate the proposed methods.
基于人工神经网络的户外导航路径识别:案例研究
导航是一个广泛的话题,一直受到移动机器人社区的广泛关注。为了在室外执行安全导航,有必要确定机器人可以穿越的地形部分和应该避开的地形部分。本文利用多层感知器神经网络分析了基于不同视觉信息的图像地形识别。利用户外机器人和摄像机在真实场景中进行了实验测试,以评估所提出的方法。
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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