Why NTU VIRAL IMU looks noisy¶
Overall: 79.8/100 · Domain: SLAM · ROS 2 · Drone platform
The headline number¶
NTU VIRAL is a strong multi-sensor drone dataset with excellent time sync (100.0 sync score) and usable GNSS (80.0). The overall score is pulled down by IMU quality at 59.5.
What drives the low IMU sub-score¶
bagx estimates IMU noise via std(diff(x))/√2 on accelerometer and gyro streams. On NTU VIRAL:
- Accelerometer and gyro noise exceed SLAM-oriented thresholds.
- High-frequency vibration and aggressive flight dynamics inflate diff-based noise estimates.
- The platform is not a static calibration rig — "noise" includes real motion content.
bagx therefore recommends LiDAR-only or LiDAR-forward SLAM (e.g. KISS-ICP) rather than tight LiDAR–IMU fusion without extra filtering or IMU denoising.
Why sync still scores 100¶
Sensor timestamps are well aligned across LiDAR, cameras, and IMU. The bag is usable; the warning is about fusion strategy, not broken recordings.
Practical takeaway¶
| Goal | Recommendation |
|---|---|
| LiDAR odometry benchmark | Good candidate — sync is clean |
| LIO with default IMU weights | Expect tuning; check IMU preprocessing |
| VIO with raw IMU | Not ideal without denoising / different noise model |
Reproduce¶
Compare with Newer College (92.3 overall) for a handheld reference bag.