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Relative pose determination of uncooperative known target based on extracting region of interest

机译:基于提取的兴趣区的不合作已知靶的相对姿态确定

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摘要

This paper deals with the problem of relative pose determination between a model-known uncooperative space target and a chaser spacecraft using three-dimensional point cloud. A novel, reliable and real-time relative pose determination framework is proposed, which is composed of a region of interest–based initial pose acquisition method and a template matching iterative closest point algorithm for tracking pose. The initial pose is obtained by the principal component analysis method which aligns the region of interest extracted from the scanning point cloud with the region of interest of the known model point cloud, and a three-dimensional convex hull is constructed to extract the region of interest fast. To improve the iterative closest point, the registration between the template point cloud generated by the pose of last frame and the point cloud of the current frame is used to replace the registration between the local scanning point cloud and the global model point cloud. In addition, the performance (stability, low cost and their robustness against noise) of the proposed initial pose acquisition method and the accuracy and reliability of the pose tracking algorithm have been demonstrated by the numerical experiments. Finally, the effectiveness of the proposed method is verified by the field experiment.
机译:本文涉及使用三维点云的模型已知的不合作空间目标和追踪空间之间的相对姿态确定问题。提出了一种新颖的,可靠和实时的相对姿势确定框架,其由基于兴趣的初始姿势采集方法和用于跟踪姿势的模板匹配的模板匹配的迭代最接近点算法组成。初始姿势是通过将从扫描点云提取的感兴趣区域与已知模型点云的感兴趣区域对准的主成分分析方法获得,并且构造了三维凸壳以提取感兴趣的区域快速地。为了改善最接近点的迭代最接近点,使用最后帧的姿势和当前帧的点云产生的模板点云之间的登记用于替换本地扫描点云和全局模型点云之间的登记。此外,通过数值实验证明了所提出的初始姿势采集方法的性能(稳定性,低成本及其对噪声的噪声)和姿势跟踪算法的准确性和可靠性。最后,通过现场实验验证了所提出的方法的有效性。

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