Calibration method of extrinsic parameters of 3D lidar and inertial sensor based on spline function

Abstract

The invention provides a method for calibrating external parameters of 3D laser radar and inertial sensor in continuous time based on spline function, and provides a method for calibrating external parameters of 3D laser radar and inertial sensor based on continuous time. The method is divided into two stages. The first stage is to preprocess the 3D laser point cloud in the calibration data based on the known environmental map. The second stage is to model the trajectory of the high-frequency inertial sensor with a spline function as Continuous trajectory, the pose of the inertial sensor at any time is obtained based on the spline function, the external parameters between the 3D lidar and the inertial sensor are introduced, the laser points are constrained, and an optimization problem is constructed to solve it. The method uses the spline function to continue the trajectory of the inertial sensor, effectively solving the difficulty of tight coupling caused by the different measurement frequencies between the sensors. This method has lower requirements on the environment, and only needs to have an open corner. The calibration results obtained by the method of the invention can be directly applied to tasks such as robot navigation and unmanned driving, and provide basic conditions for multi-sensor data fusion.

Description

technical field [0001] The invention relates to the field of multi-sensor calibration, in particular to the technical field of external parameter calibration of 3D laser radar and inertial sensors. Background technique [0002] In recent years, the field of unmanned driving has developed well, and a very important factor is the popularity of lidar. The wiring harness of lidar is getting higher and higher, the price is getting lower and lower, and the ranging capability is getting stronger and stronger. These changes will promote the unmanned driving industry to land as soon as possible. Generally speaking, unmanned vehicles will be equipped with many complementary sensors, such as lidar, camera, millimeter wave radar, inertial sensor, etc. The premise of multi-sensor data fusion is that the internal and external parameters between the sensors have a relatively good calibration result. There are many works on calibration between cameras, calibration between cameras and iner...

AI Technical Summary

Problems solved by technology

[0004] At present, the commonly used compensation method is linear interpolation between frames, that is, the assumption of uniform velocity. In the calibration scene, the sensor needs to shake violently. Obviously, the assumption of uniform velocity cannot be established, and linear interpolation cannot be applied.

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