SensorX2car: Sensors-to-car calibration for autonomous driving in road scenarios

The performance of sensors in the autonomous driving system is fundamentally limited by the quality of sensor calibration. Sensors must be well-located with respect to the car-body frame before they can provide meaningful localization and environmental perception. However, while many online methods are proposed to calibrate the extrinsic parameters between sensors, few studies focus on the calibration between sensor and vehicle coordinate system. To this end, we present SensorX2car, a calibration toolbox for the online calibration of sensor-to-car coordinate systems in road scenes. It contains four commonly used sensors: IMU (Inertial Measurement Unit), GNSS (Global Navigation Satellite System), LiDAR (Light Detection and Ranging), Camera, and millimeter-wave Radar. We design a method for each sensor respectively and mainly calibrate its rotation to the car-body. Real-world and simulated experiments demonstrate the accuracy and generalization capabilities of the proposed method. Meanwhile, the related codes have been open-sourced to benefit the community. To the best of our knowledge, SensorX2car is the first open-source sensor-to-car calibration toolbox. The code is available at https://github.com/OpenCalib/SensorX2car.