Spatiotemporal Calibration Method of Airborne Multi-Sensor via Dual-IMU Continuous-Time Optimization

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Key Points

The research aims to develop a new calibration method for airborne multi-sensors that reduces dependency on artificial targets and prior knowledge.
Introduced a dual-IMU continuous-time optimization approach for modeling sensor data.
Unified Camera, LiDAR, and dual-IMU poses within a continuous trajectory framework.
Constructed a constraint factor graph integrating IMU kinematic factors, LiDAR geometry factors, and visual reprojection factors.
Achieved online calibration of airborne multi-sensor spatial-temporal relationships with comparable accuracy to target-based methods.
Demonstrated improved system robustness and adaptability post sensor fusion.
Eliminated reliance on environmental features for calibration.

Demonstrates efficient calibration of airborne multi-sensor systems, highlighting improved accuracy without prior targets or knowledge.

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Liu et al. (2026) studied this question.

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