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Fusing Visual and Incrtial Sensing to Recover Robot Ego-motion

机译:融合视觉和刺激感应以恢复机器人的自我运动

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摘要

A method for estimating mobile robot ego-motion is presented, which relies on tracking contours in real-time images acquired with a calibrated monocular video system. After fitting an active contour to an object in the image, 3D motion is derived from the affine deformations suffered by the contour in an image sequence. More than one object can be tracked at the same time, yielding some different pose estimations. Then, improvements in pose determination are achieved by fusing all these different estimations. Inertial information is used to obtain better estimates, as it introduces in the tracking algorithm a measure of the real velocity. Inertial information is also used to eliminate some ambiguities arising from the use of a monocular image sequence. As the algorithms developed are intended to be used in real-time control systems, considerations on computation costs are taken into account.
机译:提出了一种估计移动机器人自我运动的方法,该方法依赖于跟踪通过校准的单眼视频系统获取的实时图像中的轮廓。在将活动轮廓拟合到图像中的对象之后,从轮廓在图像序列中遭受的仿射变形得出3D运动。可以同时跟踪多个对象,从而产生一些不同的姿势估计。然后,通过融合所有这些不同的估计来实现姿势确定的改进。惯性信息用于获得更好的估计,因为它在跟踪算法中引入了对实际速度的度量。惯性信息还用于消除由于使用单眼图像序列而引起的一些歧义。由于开发的算法旨在用于实时控制系统,因此需要考虑计算成本。

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