Spline function-based external parameter calibration method for 3D laser radar and inertial sensor at continuous time

Abstract

The invention provides a spline function-based external parameter calibration method for a 3D laser radar and an inertial sensor at continuous time. The method is divided into two stages, wherein thefirst stage is to preprocess 3D laser point cloud in calibration data based on a known environment map; and the second stage is to model a motion track of a high-frequency inertial sensor into a continuous track by using a spline function, obtain a pose of the inertial sensor at any moment based on the spline function, introduce an external parameter between the 3D laser radar and the inertial sensor, constrain a laser point, construct an optimization problem and solve the problem. According to the method, the track of the inertial sensor is serialized by utilizing the spline function, so thatthe difficulty of tight coupling caused by different measurement frequencies between the sensors is effectively solved. The method is relatively low in environmental requirement and only needs an open wall corner. A calibration result obtained by the method can be directly applied to tasks of robot navigation, unmanned driving and the like, so that basic conditions are provided 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...

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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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