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🛠️ Run S-Graphs On Your Data

  1. Define the transformation between your sensors (LIDAR, IMU, GPS) and base_link of your system using static_transform_publisher (see line, s_graphs_launch.py). All the sensor data will be transformed into the common base_link frame, and then fed to the SLAM algorithm. Note: base_link frame in virtual dataset is set to base_footprint and in real dataset is set to body. You can set the frames, topics for your dataset easily during the launch execution as follows:
ros2 launch lidar_situational_graphs s_graphs_launch.py compute_odom:=true lidar_topic:=/rs_lidar/points
  1. If you have an odometry source convert it to base ENU frame, then set the arg compute_odom to false in s_graphs_ros2_launch.py and then remap odom topic in s_graphs_node like
ros2 launch lidar_situational_graphs s_graphs_launch.py compute_odom:=false lidar_topic:=/rs_lidar/points odom_topic:=/odom

Info

If you want to visualize the tfs correctly from your odom source, you MUST provide a tf from the odom to base_link frame.