A method and system for laser-imu external parameter calibration

Abstract

This disclosure proposes a method and system for laser-IMU external parameter calibration, which acquires IMU measurement data and lidar measurement data; performs IMU pre-integration on the obtained IMU measurement data, and calculates the relative IMU initial The estimated value of the IMU pose transformation of the pose, according to the estimated value and the actual measured value of the IMU at the next moment, obtains the associated residual of the data association; processes the measured data of the lidar, and uses the IMU pre-integration to obtain multiple lidars Points are reprojected to the projection coordinates of the world coordinate system, and the reprojection error of each lidar point to the calibration target map is calculated; the nonlinear least square method is used to iteratively optimize the lidar-IMU external parameter calibration to obtain the external parameter calibration result. It solves the problem that the mechanical external parameters are not easy to obtain in the laser-IMU external parameter calibration, the manual measurement error is large, and the measurement is troublesome. To a certain extent, the respective shortcomings of the laser radar and the IMU can be made up for each other, and the pose of the SLAM method can be improved. Solution accuracy and speed.

Description

technical field [0001] The present disclosure relates to the technical field related to robots, and in particular, relates to a method and system for calibrating external parameters of a laser-IMU. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] In recent years, the robotics industry has proposed various multi-sensor fusion approaches for simultaneous localization and mapping, all of which rely on precise external calibration and synchronization between sensing devices. The robot is in a lack of map information and no GPS environment, such as indoors, forests, and mines. The robot's SLAM (Simultaneous Localization and Mapping) technology plays an important role. In the simultaneous positioning and mapping process, the real-time and accuracy of the solution of the robot pose directly determines the effect of SLAM mapping. [0004] Iner...

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Problems solved by technology

[0005] In order to solve the above problems, the present disclosure proposes a method and system for laser-IMU external parameter calibration, realizes tight coupling between Lidar and IMU, accurately calibrates laser-IMU external parameters, and solves the problem of laser-IMU external parameters. In the parameter calibration, the mechanical external parameters are not easy to obtain, the manual measurement error is large, and the measurement is troublesome. To a certain extent, the respective shortcomings of the Lidar (Lidar) and the IMU can be compensated for each other, which can improve the pose solution accuracy and pose of the SLAM method. Velocity, the external parameter calibration method of the present disclosure can be applied to the combined system of LiDAR-IMU two kinds of sensors

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