kalman_pos ROS 2 package

Kálmán filter based ROS 2 node (geometry_msgs/PoseStamped, sensor_msgs/Imu)

• geometry_msgs/PoseStamped
• sensor_msgs/Imu

Build

IMU transformer is a dependency, it might be needed if the IMU is not in the center of gravity (COG)

sudo apt install ros-$ROS_DISTRO-imu-transformer

cd ~/ros2_ws/src 

[!CAUTION] If you want the full compatiblity with our paper, please use release version 0.3.0. Newer releases use modified paramters. Either clone this version:

git clone https://github.com/jkk-research/kalman_pos --branch v.0.3.0

Or clone the latest version:

git clone https://github.com/jkk-research/kalman_pos

cd ~/ros2_ws

colcon build --symlink-install --packages-select kalman_pos

ROS publications / subscriptions

The main node is kalman_pos_node, also there is a vehicle_status_convert node for converting the vehicle status message to the required format.

flowchart LR

A[ /imu<br/>sensor_msgs/Imu] --> F(kalman_pos)
B[ /current_pose<br/>geometry_msgs/PoseStamped] --> F
C[ /vehicle_status<br/>geometry_msgs/Twist] --> F
D[ /nova_fix<br/>sensor_msgs/NavSatFix] --> F
E[ /duro_status<br/>std_msgs/String] --> F
F -->  G[ /estimated_pose_cog<br/>geometry_msgs/PoseStamped]
F -->  H[ /estimated_pose_baselink<br/>geometry_msgs/PoseStamped]
F -->  I[ /distance<br/>std_msgs/Float32]
F -->  J[ /estimated_trav_dist_est_pos<br/>std_msgs/Float32]
F -->  K[ /estimation_accuracy<br/>visualization_msgs/Marker]

V1(vehicle_status_convert <br> -optional-) -.-> C
V3[ /vehicle_speed <br/> std_msgs/Float32] --> V1
V4[ /vehicle_steering <br/> std_msgs/Float32] --> V1


classDef light fill:#34aec5,stroke:#152742,stroke-width:2px,color:#152742  
classDef dark fill:#152742,stroke:#34aec5,stroke-width:2px,color:#34aec5
classDef white fill:#ffffff,stroke:#152742,stroke-width:2px,color:#152742
classDef red fill:#ef4638,stroke:#152742,stroke-width:2px,color:#fff
classDef dashed fill:#ef4638,stroke:#152742,stroke-width:3px,stroke-dasharray:5,5,color:#fff

class F red
class V1 dashed
class A,B,C,D,E,G,H,I,J,K,V3,V4 light

Run

ros2 launch kalman_pos kalman_pos_node.launch.py

Parameters

• pose_topic
  • type: string
  • default value: gps/duro/current_pose
  • description: the name of the GNSS position topic (subscriber, geometry_msgs::PoseStamped)
• vehicle_status_topic
  • type: string
  • default value: vehicle_status
  • description: the name of the vehicle status topic (subscriber, autoware_msgs::VehicleStatus)
• nav_sat_fix_topic
  • type: string
  • default value: gps/nova/fix
  • description: the name of the Novatel NavSatFix topic (relevant only for Novatel GNSS) (subscriber, sensor_msgs::NavSatFix)
• imu_topic
  • type: string
  • default value: imu/data
  • description: the name of the IMU data topic (subscriber, sensor_msgs::Imu)
• est_cog_topic
  • type: string
  • default value: estimated_pose_cog
  • description: the name of the estimated position topic (transformed into the CoG) (Publisher, geometry_msgs::PoseStamped)
• est_trav_distance_odom_topic
  • type: string
  • default value: distance
  • description: the name of the estimated traveled distance position topic (calculation is based on the odemetry) (Publisher, std_msgs::Float32)
• est_trav_distance_est_pos_topic
  • type: string
  • default value: estimated_trav_dist_est_pos
  • description: the name of the estimated traveled distance position topic (calculation is based on the estimated position) (Publisher, std_msgs::Float32)
• est_baselink_topic
  • type: string
  • default value: estimated_pose_baselink
  • description: the name of the estimated position topic (transformed into the baselink) (Publisher, geometry_msgs::PoseStamped)
• est_accuracy_topic
  • type: string
  • default value: estimation_accuracy
  • description: the name of the estimattion accuracy marker topic (Publisher, visualization_msgs::Marker)
• loop_rate_hz
  • type: int
  • default value: 60
  • description: the ROS loop rate of the node (in Hz)
• estimation_method
  • type: int
  • default value: 8
  • description: the estimation method
    • 0: Kinematic model with EKF and without GNSS position; initial GNSS based orientation estimation disabled
    • 1: Kinematic + dynamic model without EKF and GNSS position; initial GNSS based orientation estimation disabled
    • 2: Kinematic model without EKF and GNSS position; initial GNSS based orientation estimation enabled
    • 3: Kinematic + dynamic model without EKF and GNSS position; initial GNSS based orientation estimation enabled
    • 4: Currently not used
    • 5: Kinematic model with EKF and without GNSS; initial GNSS based orientation estimation disabled
    • 6: Kinematic + dynamic model with EKF and without GNSS position; initial GNSS based orientation estimation disabled (USE THIS AS DEFAULT FOR ESTIMATION WITHOUT GNSS)
    • 7: Kinematic model with EKF and without GNSS position; initial GNSS based orientation estimation enabled
    • 8: Kinematic + dynamic model with EKF and without GNSS position; initial GNSS based orientation estimation enabled
    • 9: Currently used for debugging
    • 10: Automatically switch between the different estimation methods
• dynamic_time_calc
  • type: bool
  • default value: true
  • description: true if the time difference is calculated between each step, false if fix value is used (1/lROSLoopRate_cl_hz)
• kinematic_model_max_speed
  • type: double
  • default value: 0.3
  • description: the speed where the algorithm switch to the dynamic model from the kinematic model
• do_not_wait_for_gnss_msgs
  • type: bool
  • default value: true
  • description: true if the algrithm in not waiting for the first positon message (use this for the algorithms without GNSS position and orientation estimation)
• msg_timeout
  • type: double
  • default value: 2000
  • description: timeout for vehicle status and IMU message, if these messages does not arrive until timeout then the estimation will stop [ms]
• vehicle_param_c1
  • type: double
  • default value: 3000
  • description: front wheel cornering stiffness (for single track model) [N/rad]
• vehicle_param_c2
  • type: double
  • default value: 3000
  • description: rear wheel cornering stiffness (for single track model) [N/rad]
• vehicle_param_m
  • type: double
  • default value: 180
  • description: mass of the vehicle [kg]
• vehicle_param_jz
  • type: double
  • default value: 270
  • description: moment of inertia (z axle) [kg*m2]
• vehicle_param_l1
  • type: double
  • default value: 0.324
  • description: CoG distance from the front axle [m]
• vehicle_param_l1
  • type: double
  • default value: 0.976
  • description: CoG distance from the rear axle [m]
• vehicle_param_swr
  • type: double
  • default value: 1.0
  • description: Steering wheel ratio

Rosbag

Download: jkk-research.github.io/dataset

Direct download of zipped MCAPs: download zip (~15 MB)

Make sure you have unzip (sudo apt-get install unzip) and:

unzip jkkds02.zip

ros2 bag play nissan_zala_50_zeg_1_0.mcap

This example bag (mcap) file can be used with:

ros2 launch kalman_pos kalman_pos_nissan1.launch.py

Cite & paper

If you use any of this code please consider citing the paper:

@Article{doi:10.1177/09544070241266281,
    title = {Localization robustness improvement for an autonomous race car using multiple extended Kalman filters},
    author = {Krisztián Enisz and István Szalay and Ernő Horváth},
    journal = {Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering},
    volume = {0},
    url = {https://doi.org/10.1177/09544070241266281},
    eprint = {https://doi.org/10.1177/09544070241266281},
    doi = {10.1177/09544070241266281}
}