SHIRT: Satellite Hardware-In-the-loop Rendezvous Trajectories Dataset

This repository contains the Satellite Hardware-In-the-loop Rendezvous Trajectory (SHIRT) dataset which consists of two rendezvous trajectory scenarios (ROE1 and ROE2) in Low Earth Orbit (LEO) created from two different image sources. One is the OpenGL-based computer graphics renderer to create the synthetic images, and the other is the TRON facility at the Space Rendezvous Laboratory (SLAB) of Stanford University which illuminates a satellite mockup model with the Earth albedo light boxes to create the lightbox images. In ROE1, the servicer maintains the along-track separation typical of a standard v-bar hold point while the target spins about one principal axis, whereas in ROE2, the servicer slowly approaches the target tumbling about two principal axes. The sequential images of the SHIRT dataset can be used to evaluate the robustness of machine learning models and vision-based navigation filters over time across domain gap.本仓库收录卫星硬件在环交会轨迹（Satellite Hardware-In-the-loop Rendezvous Trajectory，缩写SHIRT）数据集。该数据集包含近地轨道（Low Earth Orbit，缩写LEO）下的两类交会轨迹场景（ROE1与ROE2），图像来源分为两类：一类为基于OpenGL的计算机图形渲染器生成的合成图像；另一类源自斯坦福大学空间交会实验室（Space Rendezvous Laboratory，缩写SLAB）的TRON设施，该设施通过地球反照光箱照射卫星模型样机以生成光箱图像。在ROE1场景中，服务航天器保持标准V-bar停靠点典型的沿轨间距，目标航天器则绕单一主轴自旋；在ROE2场景中，服务航天器缓慢靠近绕双主轴翻滚的目标航天器。SHIRT数据集的序列图像可用于评估机器学习模型与基于视觉的导航滤波器在跨域偏移场景下随时间变化的鲁棒性。

搜集汇总

背景与挑战

背景概述

SHIRT数据集是一个卫星硬件在轨交会轨迹数据集，包含两个低地球轨道交会场景（ROE1和ROE2），基于合成和光箱图像源生成，用于评估机器学习模型和视觉导航滤波器的跨域鲁棒性。