Astrobee ISS Free-Flyer Datasets for Space Intra-Vehicular Robot Navigation Research
IEEE ROBOTICS AND AUTOMATION LETTERS(2024)
摘要
We present the first annotated benchmark datasets for evaluating free-flyer visual-inertial localization and mapping algorithms in a zero-g spacecraft interior. The Astrobee free-flying robots that operate inside the International Space Station (ISS) collected the datasets. Space intra-vehicular free-flyers face unique localization challenges: their IMU does not provide a gravity vector, their attitude is fully arbitrary, and they operate in a dynamic, cluttered environment. We extensively evaluate state-of-the-art visual navigation algorithms on these challenging Astrobee datasets, showing superior performance of classical geometry-based methods over recent data-driven approaches. The datasets include monocular images and IMU measurements, with multiple sequences performing a variety of maneuvers and covering four ISS modules. The sensor data is spatio-temporally aligned, and extrinsic/intrinsic calibrations, ground-truth 6-DoF camera poses, and detailed 3D CAD models are included to support evaluation. The datasets are available at: https://astrobee-iss-dataset.github.io/.
更多查看译文
关键词
Navigation,Robots,Cameras,Visualization,Robot vision systems,Space vehicles,Location awareness,Data Sets for SLAM,Space Robotics and Automation,SLAM,Autonomous Vehicle Navigation
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要