Note: discontinued and incorporated into larger project here: https://github.com/tjards/swarming_sim
This project implements an autonomous, decentralized dynamic encirclement strategy for swarms of vehicles. The strategy requires no human invervention once the target is selected and all vehicles rely on local knowledge only. Each vehicle makes its own decisions about where to go based on its relative position to other vehicles, but the protocol results in a globally stable, evenly-spaced swarm.
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-2021, title={Technical Report on Structured Swarming: Dynamic Encirclement}, author={Jardine, P.T.}, year={2021}, institution={Royal Military College of Canada, Kingston, Ontario}, type={Technical Report}, }
Alternatively, you can cite any of my related papers, which are listed in Google Scholar.
This work is related to the following research in multi-agent robotics:
Ahmed T. Hafez; Anthony J. Marasco; Sidney N. Givigi; Mohamad Iskandarani; Shahram Yousefi; and Camille Alain Rabbath, "Solving Multi-UAV Dynamic Encirclement via Model Predictive Control", IEEE Transactions on Control Systems Technology, Vol. 23 (6), Nov 2015
Reza Olfati-Saber, "Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory", IEEE Transactions on Automatic Control, Vol. 51 (3), Mar 2006.
Below are several animated plots showing the behaviour of the swarm.
