Direct 6-DoF Pose Estimation from Point-Plane Correspondences

K. Khoshelham
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引用次数: 12

Abstract

Localizing a mobile sensor in an indoor environment usually involves obtaining 3D scans of the environment and estimating the sensor pose by matching the successive scans. This can be done effectively by minimizing point-plane distances for which only iterative solutions are available. Iterative solutions are notorious for convergence issues, and are inefficient for long sequences of scans. This paper presents a direct method for estimating 6-dof pose of a sensor by minimizing point-plane distances. Through experimental evaluation it is shown that the direct method gives accurate estimates, and performs robustly in presence of noise. The performance of the direct method is also evaluated with point clouds of different scale, poor plane configurations and large numbers of points and planes. A MATLAB implementation of the direct solution is available at: http://people.eng.unimelb.edu.au/kkhoshelham/research.html#directmotion.
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直接从点平面对应的六自由度姿态估计
在室内环境中定位移动传感器通常需要获取环境的三维扫描,并通过匹配连续扫描来估计传感器的姿态。这可以通过最小化只有迭代解可用的点平面距离来有效地完成。迭代解决方案因收敛问题而臭名昭著,并且对于长序列的扫描来说效率低下。本文提出了一种利用最小点平面距离直接估计传感器六自由度位姿的方法。实验结果表明,该方法具有较好的估计精度,在噪声条件下具有较好的鲁棒性。在不同尺度的点云、较差的平面构型以及大量的点和面情况下,对直接方法的性能进行了评价。直接解决方案的MATLAB实现可在:http://people.eng.unimelb.edu.au/kkhoshelham/research.html#directmotion。
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