On-line recognition of driving road condition using Support Vector Machine

Tatsuhito Watanabe, S. Katsura
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引用次数: 2

Abstract

A person operating a mobile robot in a remote environment receives a realistic visual feedback about the condition of the road on where the mobile robot is moving. A categorization of the road condition is necessary to evaluate the condition for safe and comfortable driving. For this purpose, the mobile robot should be capable of recognizing and classifying the condition of the road surfaces. In a previous research, author proposed a method to recognize the type of the road surfaces on the basis of the friction between the mobile robot and the road surfaces. The friction is estimated by a reaction torque observer, and a Support Vector Machine (SVM) is used to classify the surfaces. In this paper, SVM is calculated on-line, and multi-class classification is realized. Moreover, the operator is given feedback of haptic information by using mobile-hapto system As a result, the operator is given visual and force feedback about road condition. By experiments, the validity of the proposed method is confirmed.
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基于支持向量机的行车路况在线识别
在远程环境中操作移动机器人的人会收到关于移动机器人正在移动的道路状况的真实视觉反馈。对道路状况进行分类是评估安全舒适驾驶状况的必要条件。为此,移动机器人应具备对路面状况的识别和分类能力。在之前的研究中,作者提出了一种基于移动机器人与路面之间的摩擦来识别路面类型的方法。摩擦力由反力观测器估计,并使用支持向量机对表面进行分类。本文采用支持向量机在线计算,实现了多类分类。此外,利用移动-hapto系统对操作者进行触觉信息反馈,从而对路况进行视觉反馈和力反馈。通过实验验证了该方法的有效性。
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