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MultiSensorsCalibration

it is a conclusion of several ways to make calibration for multi-sensors

雷达-IMU标定方案

  1. 苏黎世理工开源方案:
    个人评价:本来是针对odmetry和lidar的标定修改后可用于IMU标定,不是针对IMU设计的,标定精度不容易提升
    链接地址:https://github.com/ethz-asl/lidar_align
    数据要求:基于rosbag的消息
    数据采集的要求:

  2. 浙大LI-Calib
    个人评价:最靠谱的一个
    链接地址:https://github.com/APRIL-ZJU/lidar_IMU_calib
    数据要求:rosbag velodyne_packets原始数据
    数据采集要求:平面多,1m范围内z轴动态,30s左右即可

  3. lidar_imu_calib
    个人评价:只能用来标定旋转量,不能标定平移量,速度较快
    链接地址:https://github.com/chennuo0125-HIT/lidar_imu_calib
    数据要求:rosbag topic为sensormessage数据
    数据采集:一分钟左右的数据,动态

  4. SensorsCalibration
    个人评价:包含多个不同组合传感器标定,激光IMU标定需要有GPS,纯IMU激光不可用。
    链接地址:https://github.com/PJLab-ADG/SensorsCalibration
    数据要求:8字型55X15范围的移动,平坦路面,静态物体 \

  5. kalibr工具箱
    个人评价:具有相机IMU标定功能,无lidar-imu标定
    链接地址:https://github.com/ethz-asl/kalibr

  6. koide3
    个人评价: 小日子发布的非常好用的Lidar-camera标定工具,支持旋转式和固态雷达
    链接地址:https://github.com/koide3/direct_visual_lidar_calibration
    数据要求: rosbag 无需处理,好使!

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