Paper Info
Title
Flocking for multi-agent dynamic systems: algorithms and theory
Abstract
In this paper, we present a theoretical framework for design and analysis of distributed flocking algorithms. Two cases of flocking in free-space and presence of multiple obstacles are considered. We present three flocking algorithms: two for free-flocking and one for constrained flocking. A comprehensive analysis of the first two algorithms is provided. We demonstrate the first algorithm embodies all three rules of Reynolds. This is a formal approach to extraction of interaction rules that lead to the emergence of collective behavior. We show that the first algorithm generically leads to regular fragmentation, whereas the second and third algorithms both lead to flocking. A systematic method is provided for construction of cost functions (or collective potentials) for flocking. These collective potentials penalize deviation from a class of lattice-shape objects called -lattices. We use a multi-species framework for construction of collective potentials that consist of flock-members, or -agents, and virtual agents associated with -agents called - and -agents. We show that the tracking/migration problem for flocks can be solved using an algorithm with a peer-to-peer architecture. Each node (or macro-agent) of this peer-to-peer network is the aggregation of all three species of agents. The implication of this fact is that "flocks need no leaders". We discuss what constitutes flocking and provide a universal definition of "flocking" for particle systems that has the same role as "Lyapunov stability" for nonlinear dynamical systems. By "universal", we mean independent of the method of trajectory generation for particles. Various simulation results are provided that demonstrate the eectiveness of our novel algorithms and analytical tools. This includes performing 2-D and 3-D flocking, split/rejoin maneuver, and squeezing maneuver for 40 to 150 agents (e.g. particles and UAVs).
Year
DOI
Venue
2006
10.1109/TAC.2005.864190
IEEE Transactions on Automatic Control
Keywords
DocType
Volume
Heuristic algorithms,Algorithm design and analysis,Vehicle dynamics,Unmanned aerial vehicles,Self-assembly,Cost function,Peer to peer computing,Lyapunov method,Distributed control,Biosensors
Journal
51
Issue
ISSN
Citations 
3
0018-9286
595
PageRank 
References 
Authors
62.08
21
2
Search Limit
100595
Name
Order
Citations
PageRank
Reza Olfati-Saber18066549.43
Richard M. Murray2123221223.70