【摘要】 针对现有移动机器人激光雷达外参标定方法在室内环境下误差较大的问题，提出一种基于Scan-to-Map匹配的外参标定方法。通过改进激光雷达自身位姿估计求解和移动机器人轮速计融合IMU数据得到里程计数据来提高标定精度。该方法能够适用于室内复杂场景，并经过实际机器人验证。改进后的标定方法在x、y和偏航角上精确度分别提升了51.5%、59.8%和148.2%,证明了所提方法的有效性和精确性。更多还原

【Abstract】 The existing extrinsic calibration method for mobile robot laser radar in indoor environments has significant errors. A scan-to-map matching-based extrinsic calibration method is proposed to address this issue. The calibration accuracy is enhanced by improving the pose estimation solution of LiDAR and fusing IMU data with mobile robot wheel odometry. This method is applicable to complex indoor environments and has been verified through practical robot experiments. The improved calibration method shows an increase in accuracy of 51.5%,59.8%,and 148.2% for x,y,and yaw angles, respectively, demonstrating the effectiveness and precision of the approach presented.更多还原