State Estimation with Kalman Filters in ROS 2 | Thisas Ranhiru Samaraweera | RoboticsDevDay 2024

[@chakradharv5118]

frequency: 20 sensor_timeout: 0.06 two_d_mode: true transform_time_offset: 0.0 transform_timeout: 0.0 print_diagnostics: true publish_tf: true map_frame: map odom_frame: odom base_link_frame: base_link world_frame: map # Odometry sensor input odom0: /odom # incoming messages at 20hz every 0.05s odom0_config: [true, true, false, false, false, true, true, false, false, false, false, false, false, false, false] odom0_queue_size: 10 odom0_nodelay: false odom0_differential: false odom0_relative: false # GPS sensor input pose0: /gps_cartesian # incoming messages at 1hz pose0_config: [true, true, false, false, false, false, false, false, false, false, false, false, false, false, false] pose0_queue_size: 10 pose0_nodelay: false pose0_differential: true pose0_relative: false i want to fuse odometery data with pose data(converted to catesian), is my odom0_config set correctly : i want to send x, y , yaw,x_dot & pose0 : i want to send x & y but im getting weird behaviour, the filtered odometery is almost matching the odometey not effecting by the gps data at all, even after drifting away can someone help me how i can configure the .yaml file to get things working i want to use the odometery for prediction & gps data for correction in ekf process (my odom data & gps data have covariances in their messgaes)