Real-time recognition of corridor under varying lighting conditions for autonomous vehicle

M. Minami, J. Agbanhan, H. Suzuki, T. Asakura
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引用次数: 2

Abstract

Recognition of a working environment is critical for an autonomous vehicle such as a mobile robot to confirm its possible intelligence. Therefore it is necessary to equip a recognition system with some sensor which can get environmental information. As an effective sensor, a CCD camera is generally thought to be useful for all kinds of mobile robots. However, it is thought to be hard to use the CCD camera for visual feedback which require to acquire the information in real-time. This research presents a corridor recognition method using the unprocessed gray-scale image, termed here as raw-image, and a genetic algorithm (GA), without any image information conversion, so as to perform the recognition process in real-time. The robustness of the method against noises in the environment, and the effectiveness of the method for real-time recognition have been verified using real corridor images.
自动驾驶车辆在不同光照条件下的通道实时识别
对于移动机器人等自动驾驶车辆来说,识别工作环境是确认其智能可能性的关键。因此,有必要为识别系统配备一些能够获取环境信息的传感器。CCD相机作为一种有效的传感器,通常被认为适用于各种移动机器人。然而,CCD相机的视觉反馈需要实时获取信息,因此被认为是难以实现的。本研究提出了一种利用未经处理的灰度图像(这里称为raw-image)和遗传算法(GA)进行走廊识别的方法,不进行任何图像信息转换,实现实时识别。利用真实走廊图像验证了该方法对环境噪声的鲁棒性和实时识别的有效性。
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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