IMU jittering when running with Ouster 64 LiDAR on ROS2 even after ptp time synchronization

Hello TixiaoShan, I am trying to run LIOSAM using an Ouster 64 LiDAR and Xsens MTi 670G 9-axis IMU on ROS2 Foxy. I used the bluespace_ai repo for the imu and the ouster_ros drivers provided by ouster for the lidar. At first when the data was not visible on the rviz screen, I got to know that there was a time synchronization issue between my ouster and imu. After using the sudo ptpd -i enxa0cec8fb57c3 -M -V which synchronized the header stamps of both the /ouster/points and /imu/data, I could observe the LIOSAM data on the rviz screen. But then I started getting the below error. [lio_sam_imuPreintegration-3] [ERROR] [1689143066.422097210] [lio_sam_imuPreintegration]: Lookup would require extrapolation at time 1689143066.255501, but only time 1689143066.262720 is in the buffer, when looking up transform from frame [base_link] to frame [lidar_link] [lio_sam_imuPreintegration-3] [WARN] [1689143067.443115554] [lio_sam_imuPreintegration]: Large velocity, reset IMU-preintegration!

https://github.com/TixiaoShan/LIO-SAM/assets/87766686/3e97b3d6-385d-4639-a55c-ed92c975a182

Please help me understand what the problem here is and help me rectify the issue. Given below is my param file. /**: ros__parameters:

# Topics
pointCloudTopic: "/ouster/points"                   # Point cloud data
imuTopic: "/imu/data"                        # IMU data
odomTopic: "odometry/imu"                    # IMU pre-preintegration odometry, same frequency as IMU
gpsTopic: "/gps_xsens"                    # GPS odometry topic from navsat, see module_navsat.launch file

# Frames
lidarFrame: "lidar_link"
baselinkFrame: "base_link"
odometryFrame: "odom"
mapFrame: "map"

# GPS Settings
useImuHeadingInitialization: true          # if using GPS data, set to "true"
useGpsElevation: false                       # if GPS elevation is bad, set to "false"
gpsCovThreshold: 2.0                         # m^2, threshold for using GPS data
poseCovThreshold: 25.0                       # m^2, threshold for using GPS data

# Export settings
savePCD: false                               # https://github.com/TixiaoShan/LIO-SAM/issues/3
savePCDDirectory: "/Downloads/LOAM/"         # in your home folder, starts and ends with "/". Warning: the code deletes "LOAM" folder then recreates it. See "mapOptimization" for implementation

# Sensor Settings
sensor: ouster                               # lidar sensor type, either 'velodyne', 'ouster' or 'livox'
N_SCAN: 64                                   # number of lidar channels (i.e., Velodyne/Ouster: 16, 32, 64, 128, Livox Horizon: 6)
Horizon_SCAN: 1024                            # lidar horizontal resolution (Velodyne:1800, Ouster:512,1024,2048, Livox Horizon: 4000)
downsampleRate: 1                            # default: 1. Downsample your data if too many
# points. i.e., 16 = 64 / 4, 16 = 16 / 1
lidarMinRange: 1.0                           # default: 1.0, minimum lidar range to be used
lidarMaxRange: 1000.0                        # default: 1000.0, maximum lidar range to be used

# IMU Settings
imuAccNoise: 3.9939570888238808e-03
imuGyrNoise: 1.5636343949698187e-03
imuAccBiasN: 6.4356659353532566e-05
imuGyrBiasN: 3.5640318696367613e-05

imuGravity: 9.80511
imuRPYWeight: 0.01

extrinsicTrans:  [ 0.0,  0.0,  0.0 ]
extrinsicRot:    [-1.0,  0.0,  0.0,
                   0.0,  1.0,  0.0,
                   0.0,  0.0, -1.0 ]
extrinsicRPY: [ 0.0,  1.0,  0.0,
               -1.0,  0.0,  0.0,
                0.0,  0.0,  1.0 ]

# LOAM feature threshold
edgeThreshold: 1.0
surfThreshold: 0.1
edgeFeatureMinValidNum: 10
surfFeatureMinValidNum: 100

# voxel filter paprams
odometrySurfLeafSize: 0.4                     # default: 0.4 - outdoor, 0.2 - indoor
mappingCornerLeafSize: 0.2                    # default: 0.2 - outdoor, 0.1 - indoor
mappingSurfLeafSize: 0.4                      # default: 0.4 - outdoor, 0.2 - indoor

# robot motion constraint (in case you are using a 2D robot)
z_tollerance: 1000.0                          # meters
rotation_tollerance: 1000.0                   # radians

# CPU Params
numberOfCores: 4                              # number of cores for mapping optimization
mappingProcessInterval: 0.15                  # seconds, regulate mapping frequency

# Surrounding map
surroundingkeyframeAddingDistThreshold: 1.0   # meters, regulate keyframe adding threshold
surroundingkeyframeAddingAngleThreshold: 0.2  # radians, regulate keyframe adding threshold
surroundingKeyframeDensity: 2.0               # meters, downsample surrounding keyframe poses   
surroundingKeyframeSearchRadius: 50.0         # meters, within n meters scan-to-map optimization
# (when loop closure disabled)

# Loop closure
loopClosureEnableFlag: true
loopClosureFrequency: 1.0                     # Hz, regulate loop closure constraint add frequency
surroundingKeyframeSize: 50                   # submap size (when loop closure enabled)
historyKeyframeSearchRadius: 15.0             # meters, key frame that is within n meters from
# current pose will be considerd for loop closure
historyKeyframeSearchTimeDiff: 30.0           # seconds, key frame that is n seconds older will be
# considered for loop closure
historyKeyframeSearchNum: 25                  # number of hostory key frames will be fused into a
# submap for loop closure
historyKeyframeFitnessScore: 0.3              # icp threshold, the smaller the better alignment

# Visualization
globalMapVisualizationSearchRadius: 1000.0    # meters, global map visualization radius
globalMapVisualizationPoseDensity: 10.0       # meters, global map visualization keyframe density
globalMapVisualizationLeafSize: 1.0           # meters, global map visualization cloud density

Below is my ros2 topic echo /imu/data output `header: stamp: sec: 1689156762 nanosec: 606412815 frame_id: imu_link orientation: x: 0.005952544044703246 y: 0.0018730583833530547 z: 0.7793466448783876 w: 0.6265620589256288 orientation_covariance:

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 angular_velocity: x: 0.002523512346670032 y: 0.0012271108571439981 z: 0.0061087324284017095 angular_velocity_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 linear_acceleration: x: 0.14233146607875827 y: 0.11354672908782959 z: 9.771704673767092 linear_acceleration_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

header: stamp: sec: 1689156762 nanosec: 606431003 frame_id: imu_link orientation: x: 0.005959950853139163 y: 0.001867177779786289 z: 0.7793502807617188 w: 0.626557469367981 orientation_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 angular_velocity: x: 0.00379905104637146 y: 0.001052767038345337 z: 0.0029958786908537154 angular_velocity_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 linear_acceleration: x: 0.15900063514709473 y: 0.1538238227367401 z: 9.762189865112305 linear_acceleration_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

header: stamp: sec: 1689156762 nanosec: 606439712 frame_id: imu_link orientation: x: 0.005967925302684307 y: 0.001866090577095747 z: 0.7793502807617188 w: 0.6265574097633363 orientation_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 angular_velocity: x: 0.004962087143212558 y: -0.0017598273698240519 z: -0.001525879022665322 angular_velocity_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0 linear_acceleration: x: 0.18896546959877014 y: 0.12667472660541537 z: 9.788558006286623 linear_acceleration_covariance:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

`

TixiaoShan / LIO-SAM

IMU jittering when running with Ouster 64 LiDAR on ROS2 even after ptp time synchronization #441

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