Optimizing Exploration with a New Uncertainty Framework for Active SLAM Systems

This repository is under construction.

Project Description

This repository contains the code and associated resources for our research on optimizing exploration in active SLAM systems through a new uncertainty framework. The data of all simulations are in data. The paper can be acceded by this link: https://arxiv.org/pdf/2506.17775

Getting Started

To use this project, clone the repository to your local machine using:

git clone https://github.com/Seba-san/UncertaintyMap.git 

Installation

Follow the instructions in instructions to build and run the Docker container, and to launch simulations.

Configuration

You can adjust the simulation parameters by modifying the parameters.yaml and/or simulaciones_planificadas.yaml files as needed.

Aditional Resources

For a visual demonstration of the system, watch our video:

Contributing

If you would like to contribute to this project, please consider:

• Submitting a pull request with your proposals.
• Opening an issue to discuss potential improvements.

TODO

• Make Gallery of images of the system

Citation

If you find this work useful in any way, please cite the following paper:

@article{sansoniOptimizing,
title={Optimizing Exploration with a New Uncertainty Framework for Active SLAM Systems},
author = {Sebastian Sansoni and Javier Gimenez and Gastón Castro and Santiago Tosetti and Flavio Capraro},
journal = {Robotics and Autonomous Systems},
volume = {193},
pages = {105059},
year = {2025},
issn = {0921-8890},
doi = {https://doi.org/10.1016/j.robot.2025.105059}
}