template.yaml

## General parameters
robot_name: "templatebot3000"
use_ekf_prior: True
use_slam_loop_closure: True
compute_camera_lidar_projection: True
number_of_cameras: 3
visualise: True
save_trajectories: False      # save the trajectories as csv files to compare with ground truth
downsample_points_cloud : True    # downsapling using pcl filter grid
vg_size_for_slam: 0.2             # downsapling voxel size for slam
vg_size_for_tsdf: 0.2             # downsapling voxel size for tsdf integration

## Parameters and calibration files
ekf_param_file: 'ekf_odom_imu_lidarslam.yaml'
lidarslam_param_file: 'lidarslam_params.yaml'
cameras_calibration_file: 'camchain.yaml'
rviz_config_file: 'olcmr_config.rviz'

## Data bag
use_bag: True
use_ros1_bag: False
bag_file: 'rosbag/bag'

## ROS2 Topics
lidar_point_cloud_topic: '/lidar/points'
imu_topic: '/IMU'
kinematic_odom_topic: '/odom'
camera1_namespace: '/cam1'
camera2_namespace: '/cam2'
camera3_namespace: '/cam3'

## Frames
map_frame: "map"
lidar_frame: "lidar"
camera1_frame: "cam1"
camera2_frame: "cam2"
camera3_frame: "cam3"
slam_frame: "slam_base_link"
ekf_frame: "ekf_base_link"

## Tf
publish_static_tf: True
lidar_tf: ['0','0','0','0','0','0']
lidar_camera_tf: ['0','0','0','0','0','0']
#Tf between lidar and first camera 
#(if using kalibr for extrinsic cameras calibration and estimated that tf, otherwise use tfs between cameras and robot base)

use_manually_defined_cameras_tf: False
camera1_tf: ['0', '0', '0', '0', '0', '0']
camera2_tf: ['0', '0', '0', '0', '0', '0']
camera3_tf: ['0', '0', '0', '0', '0', '0']