A view-based outdoor navigation using object recognition robust to changes of weather and seasons
A view-based outdoor navigation using object recognition robust to changes of weather and seasons
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DOI：
10.1109/iros.2003.1249323
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发表时间：
2003-10
期刊：
影响因子：
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通讯作者：
Hiroaki Katsura;J. Miura;M. Hild;Y. Shirai
中科院分区：
文献类型：
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作者：
Hiroaki Katsura;J. Miura;M. Hild;Y. Shirai
提出了一种基于视点的室外导航方法。在该方法中，用户首先沿路线沿着引导机器人。在这种引导运动中，机器人学习一系列图像和路线的粗略几何形状。然后，机器人沿着路线自主地沿着移动，并基于学习图像和输入图像之间的比较来定位自身。由于图像中的对象的外观可能根据室外场景中的季节和天气的变化而变化很大，因此简单的图像比较不起作用。因此，我们提出了一种比较方法，其中机器人首先使用允许外观变化的对象模型识别图像中的对象，然后比较学习和输入图像的识别结果。我们还开发了一种方法，自动选择关键图像用于从图像序列的比较。在不同条件下的自主导航实验表明了该方法的可行性。
This paper describes a view-based outdoor navigation method. In the method, a user first guides a robot along a route. During this guided movement, the robot learns a sequence of images and a rough geometry of the route. The robot then moves autonomously along the route with localizing itself based on the comparison between the learned images and input images. Since appearances of objects in images may vary much according to changes of seasons and weather in outdoor scenes, a simple image comparison does not work. We, therefore, propose a comparison method in which the robot first recognizes objects in images using object models which allow for appearance variations, and then compares recognition results of learned and input images. We also developed a method which automatically selects key images used for the comparison from an image sequence. Successful autonomous navigation experiments in our campus under various conditions show the feasibility of the method.