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VISION BASED PERSISTENT LOCALIZATION OF A HUMANOID ROBOT FOR LOCOMOTION TASKS

机译:基于视觉的类人机器人机器人的持久定位

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Typical monocular localization schemes involve a search for matches between reprojected 3D world points and 2D image features in order to estimate the absolute scale transformation between the camera and the world. Successfully calculating such transformation implies the existence of a good number of 3D points uniformly distributed as reprojected pixels around the image plane. This paper presents a method to control the march of a humanoid robot towards directions that are favorable for visual based localization. To this end, orthogonal diagonalization is performed on the covariance matrices of both sets of 3D world points and their 2D image reprojections. Experiments with the NAO humanoid platform show that our method provides persistence of localization, as the robot tends to walk towards directions that are desirable for successful localization. Additional tests demonstrate how the proposed approach can be incorporated into a control scheme that considers reaching a target position.
机译:典型的单眼定位方案涉及在重新投影的3D世界点和2D图像特征之间进行匹配搜索,以估计相机和世界之间的绝对比例转换。成功地计算出这样的变换意味着存在大量3D点,这些点均匀分布为围绕图像平面的重新投影像素。本文提出了一种方法,可以控制人形机器人朝有利于基于视觉的定位的方向前进。为此,对两组3D世界点及其2D图像重投影的协方差矩阵执行正交对角化。使用NAO类人动物平台的实验表明,我们的方法提供了定位的持久性,因为机器人趋向于成功定位所需的方向。其他测试证明了如何将建议的方法纳入考虑达到目标位置的控制方案。

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