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Image Feature Significance for Self-position Estimation with Variable Processing Time

机译:可变处理时间的自定位估计的图像特征意义

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We have researched about an action planning method of an autonomous mobile robot with a real-time search. In the action planning based on a real-time search, it is necessary to balance the time for sensing and time for action planning in order to use the limited computational resources efficiently. Therefore, we have studied on the sensing method whose processing time is variable and constructed a self-position estimation system with variable processing time as an example of sensing. In this paper, we propose a self-position estimation method of an autonomous mobile robot based on image feature significance. In this method, the processing time for self-position estimation can be varied by changing the number of image features based on its significance. To realize this concept, we conceive the concepts of the significance on image features, and verify three kinds of equations which respectively express the significance of image features.
机译:我们研究了一个具有实时搜索的自主移动机器人的行动规划方法。在基于实时搜索的行动规划中,有必要平衡动作规划的感测和时间的时间,以便有效地使用有限的计算资源。因此,我们已经研究了处理时间是可变的,并且构造具有可变处理时间的自定位估计系统作为感测的示例。在本文中,我们提出了一种基于图像特征意义的自主移动机器人的自定位估计方法。在该方法中,可以通过基于其意义改变图像特征的数量来改变自定位估计的处理时间。为了实现这一概念,我们构思了图像特征的重要性的概念,并验证了三种等式,分别表达了图像特征的重要性。

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