Lidar pointcloud just 1 straight line

[RBinnenmars]

I have a problem with trying to use Fast-lio with the following sensors IMU: Xsense MTI-300 Lidar: Hesai Pandar XT-32

Because the repo did not have a way to handle the Pointcloud messages from the Hesai pandar, a Pander handler function was added to the preprocess.cpp and .h files, which was retrieved from another issue for the repo that also uses . After setting everything up and determining the rotation between lidar and imu, there were some issues. The sensors were not synchronized, after adding a "time_offset_lidar_to_imu" a point cloud was visualized, which can be seen in the figure below. The point cloud is just several individual lines and not a rectangular room as was measured, hope someone can help me with this.

The possible sources, that I can think of, for this error, are: Time synchronization, extrinsic transformation, or a coding error.

common: lid_topic: "/hesai/pandar" imu_topic: "/imu/data/"
time_sync_en: false time_offset_lidar_to_imu: 130253573.95681909

preprocess: lidar_type: 4 # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR, scan_line: 32 timestamp_unit: 3 # the unit of time/t field in the PointCloud2 rostopic: 0-second, 1-milisecond, 2-microsecond, 3-nanosecond. blind: 3

mapping: acc_cov: 0.1 gyr_cov: 0.1 b_acc_cov: 0.0001 b_gyr_cov: 0.0001 fov_degree: 360 det_range: 120.0 extrinsic_est_en: false # true: enable the online estimation of IMU-LiDAR extrinsic extrinsic_T: [ 0,0.075,-0.075] extrinsic_R: [ 0, -1, 0 0, 0, 1, -1, 0, 0]

publish: path_en: false scan_publish_en: true # false: close all the point cloud output dense_publish_en: true # false: low down the points number in a global-frame point clouds scan. scan_bodyframe_pub_en: true # true: output the point cloud scans in IMU-body-frame

pcd_save: pcd_save_en: true interval: -1

[RBinnenmars]

I saw that a comma was missing in the extrinsic_R variable, now the point cloud looks like the this but the lines are still small, anyone any ideas.

[RBinnenmars]

this is/was a timing issue, recorded another bag file where the time was synchronized and the point cloud was much better