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Uncooperative pose estimation with a LIDAR-based system

机译：基于LIDAR的系统不合作的姿势估计

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This paper aims at investigating the performance of a LIDAR-based system for pose determination of uncooperative targets. This problem is relevant to both debris removal and on-orbit servicing missions, and requires the adoption of suitable electro-optical sensors on board of a chaser platform, as well as model-based techniques for target detection and pose estimation. In this paper, a three dimensional approach is pursued in which the point cloud generated by a LIDAR is exploited for pose estimation. Specifically, the condition of close proximity flight to a large debris is considered, in which the relative motion determines a large variation of debris appearance and coverage in the sensor field of view, thus producing challenging conditions for pose estimation. A customized three dimensional Template Matching approach is proposed for fast and reliable pose initial acquisition, while pose tracking is carried out with an Iterative Closest Point algorithm exploiting different measurement-model matching techniques. Specific solutions are envisaged to speed algorithm convergence and limit the size of the point clouds used for pose initial acquisition and tracking to allow autonomous on-board operation. To investigate proposed approach effectiveness and achievable pose accuracy, a numerical simulation environment is developed implementing realistic debris geometry, debrischaser close-proximity flight, and sensor operation. Results demonstrate algorithm capability of operating with sparse point clouds and large pose variations, while achieving sub-degree and sub-centimeter accuracy in relative attitude and position, respectively. (C) 2014 IAA. Published by Elsevier Ltd. All rights reserved.
机译：本文旨在研究基于激光雷达的系统对不合作目标的姿态确定的性能。这个问题与碎片清除和在轨维修任务有关，需要在追赶者平台上采用合适的光电传感器，以及用于目标检测和姿态估计的基于模型的技术。本文采用三维方法，利用激光雷达产生的点云进行姿态估计。具体地，考虑到大碎片的近距离飞行的条件，其中相对运动确定了传感器视场中的碎片外观和覆盖范围的较大变化，因此产生了用于姿势估计的挑战性条件。提出了一种定制的三维模板匹配方法，用于快速，可靠地获取姿态初始值，同时利用迭代最近点算法利用不同的测量模型匹配技术进行姿态跟踪。设想了特定的解决方案，以加快算法的收敛速度，并限制用于姿态初始获取和跟踪的点云的大小，以允许自主车载操作。为了研究拟议的进近方法的有效性和可达到的姿态精度，开发了一种数值模拟环境，该环境实现了逼真的碎片几何形状，碎片清除器近距离飞行和传感器操作。结果表明，该算法具有处理稀疏点云和较大姿态变化的能力，同时分别在相对姿态和位置上实现了亚度和亚厘米的精度。 （C）2014 IAA。由Elsevier Ltd.出版。保留所有权利。

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