Self-Assessment and Monitoring Module for Tracking Algorithms: Implementation in the Stone Soup Framework
This repository contains the implementation of self-assessment extensions for the Stone Soup framework. These extensions are part of our ongoing research on performance monitoring in tracking systems.
For more technical details, please refer to our upcoming publication.
Our proposal introduces a Self-Assessment (SA) module, referred to as Self-Assessor, into the Stone Soup framework. The module enables tracking algorithms to monitor and evaluate their own performance in real-time, facilitating more reliable decision-making in autonomous systems.
If you find this repository useful in your research, please consider citing our work.
[The citation details will be updated once the paper is published.]
@misc{aduulmstonesoup2025,
title={Self-Assessment and Monitoring Module for Tracking Algorithms: Implementation in the Stone Soup Framework},
author={Griebel, Thomas and Buchholz, Michael and Dietmayer, Klaus},
howpublished = {\url{https://github.com/uulm-mrm/aduulm-stonesoup}},
year={2025}
}
The following publications are included in the self-assessment framework:
- Kalman Filter Meets Subjective Logic: A Self-Assessing Kalman Filter Using Subjective Logic
- Self-Assessment for Single-Object Tracking in Clutter Using Subjective Logic
- Online Performance Assessment of Multi-Sensor Kalman Filters Based on Subjective Logic
To start developing with our self-assessment extensions, please use Python 3.12 and clone the appropriate branch:
git clone "https://github.com/uulm-mrm/aduulm-stonesoup.git"
cd Stone-Soup
python -m pip install -e ".[dev,aduulm]"
Make sure to check out our self-assessment extensions branch: selfassessment_extensions
If you want to experiment with the Self-Assessor, tutorials can be found here:
These tutorials allow you to:
- Disturb and manipulate ground truth trajectories
- Disturb and manipulate measurements
- Obtain self-assessment results to detect disturbances
Please note that we are still in the process of refactoring and finalizing the code. Additional tutorials and corresponding self-assessor implementations will be uploaded shortly.
--- Here begins the original Stone Soup README ---
The following section contains the unmodified README from the original Stone Soup project.
Stone Soup is a software project to provide the target tracking and state estimation community with a framework for the development and testing of tracking and state estimation algorithms.
An article is available that details the background to the project, and contains links to sample data.
Please see the Stone Soup documentation for more information.
Please see the tutorials,
examples,
and demonstrations,
which you can also try out on Binder:
Stone Soup is released under MIT License. Please see License for details.