Odyssey: An automotive lidar-inertial odometry dataset with GNSS-denied situations

The development and evaluation of Lidar-Inertial Odometry (LIO) and Simultaneous Localization and Mapping (SLAM) systems require a precise reference trajectory. The Global Navigation Satellite System (GNSS) is often used as a foundation for this, but its signals can be unreliable in obstructed environments due to multi-path effects or loss-of-signal. While existing datasets compensate for sporadic GNSS loss by incorporating Inertial Measurement Unit (IMU) measurements, the commonly used systems do not permit prolonged study of GNSS-denied environments due to accumulated drift. Consequently, existing automotive benchmarks are typically restricted to short GNSS-denied segments. To close this gap, we present Odyssey, an automotive LIO dataset featuring: (1) prolonged, previously unseen GNSS-denied environments with reference trajectories enabled by a navigation-grade Ring Laser Gyroscope (RLG)-based RTK/INS; (2) a large and diverse collection of 36 sequences that range from rural outdoor environments to urban and indoor scenarios; and (3) experimentally validated uncertainties, allowing for precise quantification of reference error. Besides providing data for LIO, Odyssey also supports place recognition tasks through threefold trajectory repetition and integration of external mapping data via precise geodetic coordinates. All data, dataloader and supplementary material are available online at https://odyssey.uni-goettingen.de/ .