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https://github.com/rwth-irt/imu-simulator
C++ Simulator and ROS 2 Node for Inertial Measurement Units.
https://github.com/rwth-irt/imu-simulator
autonomous-robots autonomous-underwater-vehicle autonomous-vehicles auv auv-simulator imu imu-sensor inertial-measurement-units inertial-sensors mems-sensors navigation robotics robotics-simulation rov sensor simulation simulator
Last synced: about 5 hours ago
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C++ Simulator and ROS 2 Node for Inertial Measurement Units.
- Host: GitHub
- URL: https://github.com/rwth-irt/imu-simulator
- Owner: rwth-irt
- License: other
- Created: 2024-04-24T07:55:17.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-07-30T09:39:42.000Z (5 months ago)
- Last Synced: 2024-11-12T02:15:07.714Z (about 2 months ago)
- Topics: autonomous-robots, autonomous-underwater-vehicle, autonomous-vehicles, auv, auv-simulator, imu, imu-sensor, inertial-measurement-units, inertial-sensors, mems-sensors, navigation, robotics, robotics-simulation, rov, sensor, simulation, simulator
- Language: C++
- Homepage:
- Size: 12.4 MB
- Stars: 5
- Watchers: 0
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT
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README
# IRT C++/ROS 2 IMU-Simulator
[](https://opensource.org/licenses/BSD-3-Clause)
**Author:**
- Maximilian Nitsch (Institute of Automatic Control - RWTH Aachen University)
**Maintainer:**
- Maximilian Nitsch (Institute of Automatic Control - RWTH Aachen University)
**Contributors:**
- Dmitrii Likhachev (Institute of Automatic Control - RWTH Aachen University)
- Philippe Panten (Institute of Flight Guidance - Technical University of Braunschweig)
## 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](#dependencies)
- [Installation](#installation)
- [Usage](#usage)
- [ROS 2 Nodes](#ros-2-nodes)
- [Publisher Node](#publisher-node)
- [Subscriber Node](#subscriber-node)
- [Coding Guidelines](#coding-guidelines)
- [References](#references)
- [Contributing](#contributing)
- [License](#license)
# Dependencies
This project depends on the following literature and libraries:
- **Eigen3**: Eigen is a C++ template library for linear algebra: [Eigen website](https://eigen.tuxfamily.org/).
- **ROS 2 Humble**: ROS 2 is a set of software libraries and tools for building robot applications: [ROS 2 Installation page](https://docs.ros.org/en/humble/Installation.html)).
# 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:
```bash
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](https://docs.ros.org/en/humble/Installation.html) 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:
```bash
mkdir -p /path/to/ros2_workspace/src
cd /path/to/ros2_workspace/src
```
Now, clone the package repository:
```bash
git clone
```
Replace `` 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:
```bash
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:
```bash
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:
```bash
ros2 launch imu_simulator_package imu_simulator.launch.py
```
The IMU simulator prints your settings and waits for a ground truth odometry message.
3. **Provide an odometry publisher** from you vehicle simulation.
For testing, you can launch the odometry_test_publisher node:
```bash
ros2 launch imu_simulator_package odometry_test_publisher.py
```
4. The IMU values should now be published.
5. 
**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:
- https://google.github.io/styleguide/cppguide.html
- http://docs.ros.org/en/humble/The-ROS2-Project/Contributing/Code-Style-Language-Versions.html
## 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](https://www.researchgate.net/publication/382562855_Navigation_of_a_Miniaturized_Autonomous_Underwater_Vehicle_Exploring_Waters_Under_Ice?_sg%5B0%5D=xNyP6RXVcEfazembhPB6cRxGQTBAvWqw6qMza26FExHUVzWcV9VUd35T4l6KjUqbo1a7W6okgPi3zqqUQYww5dmfZgsQcoJlvBE3ss1T.JLcM4K_iQyfJO7N73P9ebOmEd0xchppKYQemo5hh6ecobLxw5ZSaPgwEvlqYcQtr25iVtPvdMorpxfHK_Oldag&_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6ImhvbWUiLCJwYWdlIjoicHJvZmlsZSIsInBvc2l0aW9uIjoicGFnZUNvbnRlbnQifX0).
- 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](https://doi.org/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:
- [AV-MATLAB-SW](https://github.com/jaffarrell/AV-Matlab-SW)
## Contributing
If you want to contribute to the project, see the [CONTRIBUTING](CONTRIBUTING) file for details.
## License
This project is licensed under the BSD-3-Clause License. See the [LICENSE](LICENSE) file for details.