newer_college_2021.yaml

## General parameters
robot_name: "newer_dataset"
use_ekf_prior: True
use_slam_loop_closure: False
compute_camera_lidar_projection: True
number_of_cameras: 3
visualise: False
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: 0.5             # downsapling voxel size for slam
vg_size_for_tsdf: 0.4             # downsapling voxel size for tsdf integration

## Parameters and calibration files
ekf_param_file: 'ekf_imu_lidarslam_newer.yaml'
lidarslam_param_file: 'lidarslam_params_newer_2021.yaml'
cameras_calibration_file: 'camchain_newer.yaml'
rviz_config_file: 'olcmr_config.rviz'

## Data bag
use_bag: True
use_ros1_bag: True
bag_file: "/data2/olcmr_rosbags/2021-07-01-10-37-38-quad-easy.bag"

## ROS2 Topics
lidar_point_cloud_topic: '/os_cloud_node/points'
imu_topic: '/os_cloud_node/imu'
kinematic_odom_topic: '/odom'
camera1_namespace: '/alphasense_driver_ros/cam0'
camera2_namespace: '/alphasense_driver_ros/cam3'
camera3_namespace: '/alphasense_driver_ros/cam4'

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

## Tf
publish_static_tf: True
lidar_tf: ['0.014', '-0.012', '-0.015', '0.018', '0', '0']
imu_camera_tf: ['-0.04746142', '0.00916453', '-0.04904955', '-1.5702677','-0.0065188','-1.5668573']
#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: True
camera1_tf: ['-0.04746142', '0.00916453', '-0.04904955', '-1.5702677','-0.0065188','-1.5668573']
camera2_tf: ['-0.00894342', '0.00921261', '-0.0583279', '-3.1372737', '0.00572', '-1.5625525' ]
camera3_tf: ['0.00642473', '0.01100503', '-0.07169764', '0.0073272','-0.0049265','-1.5728354' ]