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

机译:支持向量机在线识别行驶路况

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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.
机译:在远程环境中操作移动机器人的人会收到有关移动机器人所行驶的道路状况的真实视觉反馈。为了评估安全和舒适驾驶的条件,必须对路况进行分类。为此,移动机器人应具有识别和分类路面状况的能力。在先前的研究中,作者提出了一种基于移动机器人与路面之间的摩擦力来识别路面类型的方法。摩擦是由反作用扭矩观测器估算的,并且使用支持向量机(SVM)对表面进行分类。本文通过在线计算支持向量机,实现了多类分类。此外,通过使用移动触觉系统向操作员提供了触觉信息的反馈。结果,为操作员提供了关于道路状况的视觉和力的反馈。通过实验,验证了所提方法的有效性。

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