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Task-oriented navigation algorithms for an outdoor environment with colored borders and obstacles

机译:面向任务导航的导航算法,用于彩色边界和障碍物

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摘要

This paper presents task-oriented navigation algorithms used for an outdoor environment. The goals of the navigation are recognizing colored border lines on both sides of a path, avoiding obstacles on the path, and navigating the given path. To recognize the colored border lines with one camera, we apply a support vector data description method, which employs six color features extracted from two color models. To avoid collision with obstacles on the path, we fuse the data of the lines measured by a camera and the obstacles measured by a laser range finder. These algorithms were applied to autonomous navigation of about 100 m long curved track. We demonstrate that a four-wheel skid-steeringmobile robot successfully finishes the mission.
机译:本文介绍了用于户外环境的面向任务导航算法。 导航的目标是在路径的两侧识别有色边界线,避免路径上的障碍物,并导航给定路径。 要识别带有一个相机的彩色边界线,我们应用了支持向量数据描述方法,该方法采用了从两种颜色模型中提取的六种颜色特征。 为了避免与路径上的障碍碰撞,我们融合了通过相机测量的线的数据和激光测距仪测量的障碍物。 这些算法应用于大约100米长的曲线的自主导航。 我们展示了一个四轮滑动转向机器人机器人成功完成了任务。

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