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Experimental Results for Image-Based Geometrical Reconstruction for Spacecraft Rendezvous Navigation with Unknown and Uncooperative Target Spacecraft

机译:与未知和不合作的目标航天器的航天器与航天器导航基于图像的几何重构实验结果

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For both manned and autonomous space on-orbit servicing missions, the collision avoidance and motion prediction of the target objects are essential for a safe mission operation. Our approach assumes unknown and uncooperative target objects (spacecraft, space debris) and a camera only vision system. The target's 3D structure is reconstructed from a sparse point cloud extracted from a rendezvous-SLAM algorithm and processed by a RANSAC algorithm. Afterwards the 3D model can be used in a feedback manner for enhancing visual navigation processing tasks. The paper details the general concept and presents experimental results with camera image data from a spacecraft rendezvous simulator testbed.
机译:对于轨道和自主空间的轨道服务任务,目标对象的碰撞避免和运动预测对于安全的任务操作至关重要。 我们的方法假设未知和不合作的目标物体(航天器,空间碎片)和相机只有视觉系统。 从从Rendezvous-SLAM算法提取的稀疏点云并由RANSAC算法处理,重建目标的3D结构。 之后,可以以反馈方式使用3D模型以增强视觉导航处理任务。 本文详细介绍了一般概念,并用来自航天器集合模拟器的相机图像数据展示了实验结果。

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