Formation Control Algorithms

We focus on the development of formation control algorithms for swarms of robots in situations where communication is not available or only minimal information is transmitted to near neighbors. Scalability and dynamic reallocation are key factors that we take into account.

The images below include an example of an arrow configuration where agents are able to measure the relative position of their neighbors, but achieve the final configuration without communication, and the simulation environment that we have developed to adjust algorithm parameters for different scenarios, as well as test the overall performance in terms of convergence speed and accuracy.


[1] Jorge Pena Queralta, Li Qingqing, Tuan Nguyen Gia, Hong-Linh Truong, Tomi Westerlund, "End-to-End Design for Self-Reconfigurable Heterogeneous Robotic Swarms", arXiv preprint , arXiv (2020) . (View) (Download) (Researchgate) (arXiv)

[2] Jorge Peña Queralta, Li Qingqing, Tuan Nguyen Gia, Zhuo Zou, Hannu Tenhunen and Tomi Westerlund, "Distributed Progressive Formation Control with One-Way Communication for Multi-Agent Systems", IEEE Symposium Series on Computational Intelligence , IEEE (2019) . (View) (Download) (Researchgate)

[3] Cassandra McCord, Jorge Peña Queralta, Tuan Nguyen Gia and Tomi Westerlund, "Distributed Progressive Formation Control for Multi-Agent Systems: 2D and 3D deployment of UAVs in ROS/Gazebo with RotorS", European Conference on Mobile Robots (ECMR) , IEEE (2019) . (View) (Download)

[4] Jorge Peña Queralta, Cassandra McCord, Tuan Nguyen Gia, Hannu Tenhunen and Tomi Westerlund, "Communication-free and Index-free Distributed Formation Control Algorithm for Multi-robot Systems", Procedia Computer Science , Elsevier (2019) . The 10th International Conference on Ambient Systems, Networks and Technologies (ANT). (View) (Download) (Researchgate)