Odyssey: An automotive lidar-inertial odometry dataset with GNSS-denied situations
Odyssey: An automotive lidar-inertial odometry dataset with GNSS-denied situations
This publication presents Odyssey, an automotive LIO dataset featuring prolonged GNSS-denied environments enabled by a navigation-grade Ring Laser Gyroscope (RLG)-based RTK/INS. The dataset includes 36 diverse sequences ranging from rural outdoor to urban and indoor scenarios, along with experimentally validated uncertainties for precise error quantification. It also supports place recognition tasks through trajectory repetition and integration of external mapping data via precise geodetic coordinates.
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The paper introduces Odyssey, a new automotive dataset designed to support Lidar-Inertial Odometry (LIO) and SLAM systems in GNSS-denied environments by utilizing a navigation-grade Ring Laser Gyroscope (RLG)-based RTK/INS for reference trajectories.
What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
sequences
36
View original evidence
tories 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 repet
Open source S4
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- code: not_reported
- weights: not_reported
What remains unknown
Dataset licensing and commercial-use rights are not established here.
Source excerpts and review record
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orating 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 trajec
Open source S3
tories 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 repet
Open source S4
Odyssey: An automotive lidar-inertial odometry dataset with GNSS-denied situations
Open source S1
ition 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/ .
Open source S5
Implications for data suppliers
RoboSignal interpretation and collection questions, not statements of buyer demand.
- Confirm the required data type and collection setting with the buyer; this source does not establish a complete collection specification.
- Compare the reported units and scope before using these quantities in a budget. Recording hours, sensor-hours and trajectories are different measures.
- Validate demand and acceptance criteria with a buyer before scaling. Publication, popularity and a research result do not establish a purchase commitment.
Source：International Journal of Robotics Research — Journal metadata · doi.org