- Visualizing tool to check quality of the map with the estimated pose of your odometry / SLAM algorithm
- It gets
TUMformat estimated pose - tx px py pz qx qy qz qw - It gets the
rosbagfile that used for pose estimation - It publishes the transformed pointcloud to estimated pose frame
- It also publishes the estimated odometry in nav_msgs/Path
- It gets
C++CMake,EigenROS1yaml-cppsudo apt install libyaml-cpp-dev
livox_ros_driverpackage for converting livox LiDAR data from many datasets- Specifically,
livox_ros_driver/CustomMsg
- Specifically,
- Get the code and then build
cd ~/your_workspace/src git clone https://github.com/engcang/tum_pcl_visualizer cd ~/your_workspace catkin build -DCMAKE_BUILD_TYPE=Release
- Run the code and watch the pointcloud with
Rvizrosrun tum_pcl_visualizer tum_pcl_visualizer_node config_file bag_file_abs_path tum_csv_file_abs_path publish_hz max_t_diff_btw_pcl_and_pose time_offset
- velodyne packets to sensor_msgs::PointCloud2
-
ROS2
- This code is coded by myself and ChatGPT and hence it is free to use, distribute, etc.
- I guess it is under BSD3 or MIT license.