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Feature based map building using sparse sonar data

机译:使用稀疏声纳数据构建基于特征的地图

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A new feature based map building model that uses only the footprints of sparse sonar data has been developed and implemented. An arc feature association model was developed, which associates two sonar footprints into an arc feature. The association model provides information on the regions of center points of the arc feature. The information makes it possible to decide weather the two sonar footprints are associated with a line, point or arc. Lines, points, or arc features are extracted from more than two independent sonar footprints using the arc feature association model. We also propose a method that estimates the position uncertainties of the extracted features by considering both the pose uncertainty of the robot and the measurement uncertainty of the sonar sensor. This pose uncertainty is also used in the arc feature association process of the sonar footprints. The proposed method has been tested in a real home environment with a mobile robot.
机译:仅开发并实现了仅基于新的要素地图建筑模型,仅使用稀疏声纳数据的脚印。开发了一个弧形功能关联模型,将两个声纳占用脚印与弧功能相关联。关联模型提供有关电弧特征的中心点区域的信息。这些信息可以决定天气,两个声纳占地面积与线,点或弧相关联。使用电弧特征关联模型从两个独立的声纳占地面积中提取线条,点或弧特征。我们还提出了一种方法,该方法通过考虑机器人的构成不确定性以及声纳传感器的测量不确定性来估计提取特征的位置不确定性。这种构成不确定性也用于声纳占地面积的电弧特征关联过程。该方法已经在具有移动机器人的真实家庭环境中进行了测试。

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