IMU/Vehicle Calibration and Integrated Localization for Autonomous Driving

The localization system, which outputs vehicle position, velocity, and attitude, is one of the fundamental components in the autonomous driving vehicle. The global pose is not only used for the planning and control system, but also an important reference for the cloud source-based HD Map building and updating. The accuracy, availability, and reliability are key requirements for the localization system to ensure that the whole system runs smoothly and efficiently.IMU/Vehicle extrinsic calibration is one of the primary jobs that should be addressed. Due to the observability issue, the IMU/vehicle relative roll cannot be calibrated by the traditional maneuver-based calibration method. In this paper, we solve this issue with the proposed Multiple Orientation-based Vehicle/IMU Extrinsic Calibration (MOVIE-Cali) method, which is evaluated by Monte Carlo simulations and experiments.When the vehicle is cornering or making a U-turn, the sideslip of the tires will have negative influence on the localization system which uses Non-Holonomic Constraints (NHC)/Wheel speed sensor measurement in the model. We derive a sideslip angle model and propose an online slip parameter calibration and compensation method to improve the localization accuracy. The performance of proposed method has been evaluated by the vehicle tests.