chengkaiqiang 6213262140 v-0.1.1-1:20240806 | 3 months ago | |
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.. | ||
include | 3 months ago | |
launch | 3 months ago | |
src | 3 months ago | |
CMakeLists.txt | 3 months ago | |
README.md | 3 months ago |
This package allows to obtain the extrinsic calibration between two PointClouds with the help of the NDT algorithm.
The multi_lidar_calibrator
node receives two PointCloud2
messages (parent and child), and an initialization pose.
If possible, the transformation required to transform the child to the parent point cloud is calculated, and output to the terminal.
You'll need to provide an initial guess, otherwise the transformation won't converge.
In a sourced terminal:
Using rosrun
rosrun multi_lidar_calibrator multi_lidar_calibrator _points_child_src:=/lidar_child/points_raw _points_parent_src:=/lidar_parent/points_raw _x:=0.0 _y:=0.0 _z:=0.0 _roll:=0.0 _pitch:=0.0 _yaw:=0.0
Using roslaunch
roslaunch multi_lidar_calibrator multi_lidar_calibrator points_child_src:=/lidar_child/points_raw points_parent_src:=/lidar_parent/points_raw x:=0.0 y:=0.0 z:=0.0 roll:=0.0 pitch:=0.0 yaw:=0.0
Play a rosbag with both lidar data /lidar_child/points_raw
and /lidar_parent/points_raw
The resulting transformation will be shown in the terminal as shown in the Output section.
Open RViz and set the fixed frame to the Parent
Add both point cloud /lidar_parent/points_raw
and /points_calibrated
If the algorithm converged, both PointClouds will be shown in rviz.
Parameter | Type | Description |
---|---|---|
points_parent_src |
String | PointCloud topic name to subscribe and synchronize with the child. |
points_child_src |
String | PointCloud topic name to subscribe and synchronize with the parent. |
voxel_size |
double | Size of the Voxel used to downsample the CHILD pointcloud. Default: 0.5 |
ndt_epsilon |
double | The transformation epsilon in order for an optimization to be considered as having converged to the final solution. Default: 0.01 |
ndt_step_size |
double | Set/change the newton line search maximum step length. Default: 0.1 |
ndt_resolution |
double | Size of the Voxel used to downsample the PARENT pointcloud. Default: 1.0 |
ndt_iterations |
double | The maximum number of iterations the internal optimization should run for. Default: 400 |
x |
double | Initial Guess of the transformation x. Meters |
y |
double | Initial Guess of the transformation y. Meters |
z |
double | Initial Guess of the transformation z. Meters |
roll |
double | Initial Guess of the transformation roll. Radians |
pitch |
double | Initial Guess of the transformation pitch. Radians |
yaw |
double | Initial Guess of the transformation yaw. Radians |
/points_calibrated
.static_transform_publisher
.transformation from ChildFrame to ParentFrame
This transformation can be replicated using:
rosrun tf static_transform_publisher 1.7096 -0.101048 -0.56108 1.5708 0.00830573 0.843 /ParentFrame /ChildFrame 10
The figure below shows two lidar sensors calibrated by this node. One is shown in gray while the other is show in blue. Image obtained from rviz.