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IRT C++/ROS 2 IMU-Simulator

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Description

This project provides a high-fidelity IMU simulator written in C++.

The simulator implements the following features:

  • Accelerometer and gyroscope measurement simulation
  • WELMEC gravity model (accelerometer)
  • WGS84 Earth angular velocity model (gyroscope)
  • Transport rate angular velocity model (gyroscope)
  • Turn-on bias
  • Scaling errors
  • Misalignment and orthogonality errors
  • Stochastic noise (colored/non-white noise)
    • Velocity/angular random walk
    • Bias instability
    • Acceleration/rate random walk
  • Saturation
  • Quantization errors
  • All parameters for an IMU can be configured in a YAML file
  • All models and effects can be enabled/disabled separately

An example configuration from real data of a STIM300 IMU is provided.

MATLAB scripts are provided to extract the stochastic noise components using Allan variance analysis. For this, you must provide a long-term (minimum six hours) dataset of acceleration/gyroscope measurements. The IMU must be static, temperature- and vibration-compensated during the recording.

Table of Contents

Dependencies

This project depends on the following literature and libraries:

  • Eigen3: Eigen is a C++ template library for linear algebra: Eigen website.
  • ROS 2 Humble: ROS 2 is a set of software libraries and tools for building robot applications: ROS 2 Installation page).

Installation

To install the imu_simulator_package, you need to follow these steps:

  1. Install Eigen3: Eigen3 is a dependency for your package. You can install it using your package manager. For example, on Ubuntu, you can install it using the following command:

    sudo apt-get install libeigen3-dev

  2. Install ROS 2 Humble: Make sure you have ROS 2 (Humble) installed. You can follow the official installation instructions provided by ROS 2. Visit ROS 2 Humble Installation page for detailed installation instructions tailored to your platform.

  3. Clone the Package: Clone the package repository to your ROS 2 workspace. If you don't have a ROS 2 workspace yet, you can create one using the following commands:

    mkdir -p /path/to/ros2_workspace/src
cd /path/to/ros2_workspace/src

    Now, clone the package repository:

    git clone <repository_url>

    Replace <repository_url> with the URL of your package repository.

  4. Build the Package: Once the package is cloned, you must build it using colcon, the default build system for ROS 2. Navigate to your ROS 2 workspace and run the following command:

    cd /path/to/ros2_workspace
colcon build

    This command will build all the packages in your workspace, including the newly added package.

  5. Source the Workspace: After building the package, you need to source your ROS 2 workspace to make the package available in your ROS 2 environment. Run the following command:

    source /path/to/ros2_workspace/install/setup.bash

    Replace /path/to/ros2_workspace with the actual path to your ROS 2 workspace.

That's it! Your imu_simulator_package should now be installed along with its dependencies and ready to use in your ROS 2 environment.

Usage

  1. Configure your YAML file for your IMU or use the default file.

  2. Start the IMU simulator with the launch file:

    ros2 launch imu_simulator_package imu_simulator.launch.py

The IMU simulator prints your settings and waits for a ground truth odometry message.

  1. Provide an odometry publisher from you vehicle simulation. For testing, you can launch the odometry_test_publisher node:

    ros2 launch imu_simulator_package odometry_test_publisher.py

  2. The IMU values should now be published.

  3. Accelerometer and gyroscope values visualized with PlotJuggler.

Important Usage Information:

  • The odometry message must be published with at least the IMU data rate/sample time.
  • The message /imu/diagnostic will show WARN if the odometry rate is lower.
  • If no odometry message is published, the message /imu/diagnostic will show STALE.
  • If everything is correct, /imu/diagnostic will show OK.

ROS 2 Nodes

The IMU simulator node implements five publishers and subscribes to one topic. ROS 2 services or actions are not provided.

Publisher Node

This node publishes the following topics:

Topic Name Message Type Description
*/imu/data sensor_msgs/Imu.msg Publishes IMU sensor data.
*/imu/data_visualization geometry_msgs/AccelStamped.msg Publishes IMU sensor data for visualization (rviz).
*/imu/true_linear_acceleration geometry_msgs/Vector3.msg Publishes Itrue linear acceleration.
*/imu/true_linear_angular_velocity geometry_msgs/Vector3.msg Publishes true angular velocity.
*/imu/diagnostic diagnostic_msgs/DiagnosticStatus.msg Publishes diagnostic status of IMU data.

Subscriber Node

This node subscribes to the following topics:

Topic Name Message Type Description
*/odometry nav_msgs/Odometry.msg Subscribes to ground truth vehicle odometry.

Coding Guidelines

This project follows these coding guidelines:

References

The IMU simulator implementation closely follows the work:

  • M. Nitsch, "Navigation of a miniaturized autonomous underwater vehicle exploring waters under ice," Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, RWTH Aachen University, 2024. DOI: 10.18154/RWTH-2024-05964.
  • J. A. Farrell, F. O. Silva, F. Rahman and J. Wendel, "Inertial Measurement Unit Error Modeling Tutorial: Inertial Navigation System State Estimation with Real-Time Sensor Calibration," in IEEE Control Systems Magazine, vol. 42, no. 6, pp. 40-66, Dec. 2022, DOI: 10.1109/MCS.2022.3209059.
  • J. A. Farrell, "Aided Navigation Systems: GPS and High Rate Sensors," New York, NY, McGraw-Hill, 552 pages, 2008.

The MATLAB scripts are in parts taken from:

Contributing

If you want to contribute to the project, see the CONTRIBUTING file for details.

License

This project is licensed under the BSD-3-Clause License. See the LICENSE file for details.