Abstract
The "Tango Spacecraft Dataset for Monocular Pose Estimation" dataset here published should be used for relative pose estimation tasks. It is split into 30002 train images and 3002 test images representing the Tango spacecraft from Prisma mission, being the largest publicly available dataset of synthetic space-borne noise-free images tailored to pose estimation tasks (up to our knowledge). The label of each image gives relative quaternion (in scalar-last format) between Tango and the camera (hence the relative position of the target with respect to the camera in camera reference frame) and the relative position of Tango with respect to the camera in camera reference frame. More information on the dataset split and on the label format are reported below. Images Information: The dataset comprises 30002 synthetic grayscale images of Tango spacecraft from Prisma mission that serves as train set, while the test set is formed by 3002 synthetic grayscale images of Tango spacecraft from Prisma mission in PNG format. About 1/6 of the images both in the train and in the test set have a non-black background, obtained by rendering an Earth-like model in the raytracing process used to define the images reported. The images are noise-free to increase the flexibility of the dataset. The illumination direction of the spacecraft in the scene is uniformly distributed in the 3D space in agreement with the Sun position constraints. The dataset contains also a .txt file with the parameters of the camera used to generate the images.
Paolo Lunghi
Assistant Professor of Aerospace Systems
Aiming for autonomous Guidance, Navigation, and Control for spacecraft.