Multi-Flock Flocking for Multi-Agent Dynamic Systems

There has been much research done on single-flock flocking Shaw (1975), Partridge (1984), Partridge (1982), Okubo (1986), Reynolds (1987), Vicsek et al. (1995), Toner & Tu (1998), Shimoyama et al. (1996), Mogilner & Edelstein-Keshet (1999), Helbing et al. (2000), Vicsek (2001), Parrish et al. (2002), Olfati-Saber (2006), but none done on multi-flock flocking Gazi & Fidan (2007). One might ask, "Why would we need multiple flock flocking?" Consider the following scenario: there are two groups (squads/flocks) of Unmanned Vehicles (UV), both being in between the other group and the other groups’ objective/goal. If both groups had the same capabilities then all we would need to do is to swap the groups goals. Unfortunately the groups have different sensing capabilities. One group of UV’s is equipped with infrared cameras and the other with high-resolution cameras. Since each group is in the way of the other, it would be great if they could move out of each other’s way. This in turn would decrease the amount of time for both groups to meet their goals. We propose a new flocking algorithm that allows flocks to maneuver around other flocks (if needed) decreasing the amount of time each flock takes to reach their respective goals. Wewill do this by adding an additional agent, τ, to Olfati-Saber’s Olfati-Saber (2006) existing α, β and γ-agents. The resulting algorithmwill be compared to Olfati-Saber’s flocking algorithm. Both algorithms will be simulated in multiple scenarios using Matlab. The scenarios will consist of both flock’s being in-between the other flock and the other flocks goal, using different size flocks and only 1 group for a baseline. Section 2 presents related works. Section 3 includes our approach and multi-flock flocking algorithm. Section 4 contains our simulation setup. The simulation results are in 5; followed by the analysis in Section 6. Conclusions and future directions are in Section 7.