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

Zhenghao Zou, Yang Lyu, Chunhui Zhao, Xirui Kao, Jiangbo Liu, Haochen Chai

Abstract: 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 suspension 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

External IDs:dblp:conf/iros/ZouL0KLC24