Simulate 2D and 3D swarms of mobile agents with various dynamics and implement distributed control laws to obtain different behaviours.
To execute your first simulation simply run Launcher.m.
Features:
- Simulation of swarms of mobile agents.
- Implement your own dynamical model or use one of the embedded ones (see
integrateAgents). - Implement your own distributed control law or use one of the embedded ones (see
globalInteractionForce). - Acquisition of metrics to evaluate the performance.
- Extensive simulations to study stochastic effects or different initial conditions (see
MultiLauncher). - Extensive simulations to study the effects of the parameters (see
SequentialLauncher). - Local stability analysis through linearization (see
CrystalStability). - Interface with Robotarium code to perform advanced simulations and real life experiments (see
RobotariumSimulator). For more details refer to https://www.robotarium.gatech.edu. - Plots to visualise the simulation and the metrics.
- Automatic save the results of the simulations.
This project implements the algorithms described in [Giusti2022] (see SwarmSimV1 ) and [Giusti2023]. In the Media folder, there is a video supplement for [Giusti2022].
For more information contact andrea.giusti@unina.it.
Copyrights: If you use this code for research purposes and want to mention it in one of your publications, please cite [Giusti2022].
Versions:
- V2.0 - Authors: Andrea Giusti. Date: 2023
- V1.1 - Authors: Andrea Giusti and Gian Carlo Maffettone. Date: 2023
- V1.0 - Authors: Andrea Giusti and Gian Carlo Maffettone. Date: 2022
References:
- [Giusti2023] Giusti, A., Coraggio, M., & di Bernardo, M. (2023). Local Convergence of Multi-Agent Systems Toward Rigid Lattices. IEEE Control Systems Letters. DOI:10.1109/LCSYS.2023.3289060.
- [Giusti2022] Giusti, A., Maffettone, G. C., Fiore, D., Coraggio, M., & di Bernardo, M. (2022). Distributed Control for Geometric Pattern Formation of Large-Scale Multirobot Systems. arXiv preprint arXiv:2207.14567.