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Package Summary
| Tags | No category tags. |
| Version | 0.0.0 |
| License | MIT |
| Build type | CATKIN |
| Use | RECOMMENDED |
Repository Summary
| Description | Code Repository for the MOOC "Automated and Connected Driving Challenges" available on edX. |
| Checkout URI | https://github.com/ika-rwth-aachen/acdc.git |
| VCS Type | git |
| VCS Version | main |
| Last Updated | 2024-10-15 |
| Dev Status | UNKNOWN |
| CI status | No Continuous Integration |
| Released | UNRELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Source code in C++ of the core object fusion functionality. Does not contain a ROS node.
Additional Links
No additional links.
Maintainers
- ACDC
Authors
No additional authors.
Object Fusion
This package contains a library that implements a multi-instance Kalman filter for object-level sensor data fusion and tracking. An overview over the functionality is given in ../README.md.
Mathematical symbols
The Kalman filter symbols in the code are:
| Symbol in code | Meaning | Symbol in ACDC slides, remarks |
|---|---|---|
x_hat_G |
Global object state vector | $\hat{x}_g$ |
globalObject.P() |
Global object state vector error covariance | $\mathbf{P_G}$ |
F |
State transition matrix (motion model matrix) | $\mathbf{F}$ |
Q |
Process noise matrix (adds noise during prediction) | $\mathbf{Q}$ |
C |
Measurement matrix (reduces global state space to measured space) | $\mathbf{C}$ |
x_hat_S |
Vector of measured and non-measured variables of the sensor-level object | $\hat{x}_S$, to get it in code: IkaUtilities::getEigenStateVec(&measuredObject)
|
z |
Vector of actually measured variables (in the measured space) | $\mathbf{z}$ |
P_S_diag |
Variance vector of measured and non-measured variables of the sensor-level object | $\mathbf{P_S}$, but only its diagonal in the code: IkaUtilities::getEigenVarianceVec(&measuredObject)
|
R |
Measured variables error covariance matrix | $\mathbf{R}$ |
S |
Innovation error covariance (or residual error covariance) | $\mathbf{S}$ |
K |
Kalman gain | $\mathbf{K}$ |
CHANGELOG
No CHANGELOG found.
Wiki Tutorials
This package does not provide any links to tutorials in it's rosindex metadata.
You can check on the ROS Wiki Tutorials page for the package.
Dependant Packages
| Name | Deps |
|---|---|
| object_fusion_wrapper |
Launch files
No launch files found
Messages
No message files found.
Services
No service files found
Plugins
No plugins found.
Recent questions tagged object_fusion at Robotics Stack Exchange
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