SwiftBase: A Dataset Based on High-Frequency Visual Measurement for Visual-Inertial Localization in High-Speed Motion Scenes

Localizing an aggressively moving platform is a considerable challenge in the SLAM domain. This paper presents a dataset, SwiftBase, crafted to facilitate research into precise localization under such conditions. It includes high-speed cameras with over 200Hz sampling rate, capturing detailed visual data for analyzing rapid external dynamics. The dataset features two IDS high-speed cameras, a low-frequency camera, and a high-precision integrated inertial measurement unit (IMU). Calibration parameters are provided, and sensor data is synchronized using ROS system time. SwiftBase is recorded in indoor environments, utilizing pulleys and suspen- sion ropes to simulate high-speed conditions, with ground truth data supplied by OptiTrack. SwiftBase has been instrumental in evaluating advanced VI-SLAM algorithms. However, there is still an urgent need for new algorithms capable of robust and real-time tracking in High-Speed localization.1