Multiagent Coordination Simulator

This project implements various multiagent coordination techniques, including:

- Reynolds rules of flocking ("boids")
- Olfati-Saber flocking
- Starling flocking
- Dynamic Encirclement 
- Heterogeneous Pinning Control
- Arbitrary Closed Curves 
- Shepherding

All agents make individual decisions based on local information only. There is no global plan. The code builds on our (now archived) earlier work in Swarming Simulator v3

Methodology

The swarming techniques above are all implemented as high-level trajectory planners, assuming underlying double integrator dynamics. When quadcopter dynamics are applicable, these command signals - which take the form of accelerations in Cartesian space - are then converted into velocity setpoints. The quadcopters make use of 3 nested control loops (translational velocity, angular position, and angular velocity) to track the desired trajectory.

Demonstrations

Video of autonomous assembly of closed curves with random arrival and depature. The closed curves include Lemniscates of Bernoulli and Gerono and a Dumbbell Curve:

This plot demonstrates the agents automatically tightening up their spacing, as more agents join the swarm:

More demonstration of lemniscates of Bernoulli, Gerono (with phase shift), and Dumbbell in a cluttered environment:

This program also implements heterogeneous Pinning Control with autonomous pin selection based on Controlability Gramian:

An illustration of Shepherding:

Also supports quadcopter dynamics:

References

1. Craig Reynolds, "Flocks, Herds, and Schools:A Distributed Behavioral Model", Computer Graphics, 21(4) (SIGGRAPH '87 Conference Proceedings), pages 25-34, 1987.
2. Reza Olfati-Saber, "Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory", IEEE Transactions on Automatic Control, Vol. 51 (3), 2006.
3. H. Hildenbrandt, C. Carere, and C.K. Hemelrijk,"Self-organized aerial displays of thousands of starlings: a model", Behavioral Ecology, Volume 21, Issue 6, pages 1349–1359, 2010.
4. P. T. Jardine and S. N. Givigi, "Bimodal Dynamic Swarms", IEEE Access, vol. 10, pp. 94487-94495, 2022.
5. P. T. Jardine and S. N. Givigi, "Flocks, Mobs, and Figure Eights: Swarming as a Lemniscatic Arch", IEEE Transactions on Network Science and Engineering, 2022.
6. Kléber M. Cabral, Sidney N. Givigi, and Peter T. Jardine, Autonomous assembly of structures using pinning control and formation algorithms in 2020 IEEE International Systems Conference (SysCon), 07 Dec 2020
7. S. Van Havermaet et al. Steering herds away from dangers in dynamic environments in Royal Society Open Science, 2023

Citing

The code is opensource but, if you reference this work in your own reserach, please cite me. I have provided an example bibtex citation below:

@techreport{Jardine-2023, title={Multiagent Coordination Simulator}, author={Jardine, P.T.}, year={2023}, institution={Royal Military College of Canada, Kingston, Ontario}, type={GitHub Repository}, }

Alternatively, you can cite any of my related papers, which are listed in Google Scholar.