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Multi-robotics systems are currently subject of major interest in the robotics literature. In the leading journals can be found hundreds of articles, published in the last few years, concerning applications and theoretical studies of small groups maintaining in fixed formation (Fua et al., 2007; Kaminka et al., 2008) as well as swarms of thousands robots (Derenick & Spletzet, 2007; Daigle et. al, 2008). The large systems can be moreover represented by work published in (Peasgood et al., 2008) where collision free trajectories to reach individual goals are designed for 100 robots. The method using graph and spanning tree representation is developed for utilization in underground mine environment. In another example (Kloetzer & Belta,2007), a large swarm of robots is controlled using hierarchical abstractions. Inter-robot collision avoidance and environment containment are there guaranteed applying centralized communication architecture. Finally work presented in (Milutinovi & Lima, 2006) applies a Stochastic Hybrid Automation model for modeling and control of multi-agent population composed of a large number of agents. In this method probabilistic description of task allocation as well as distribution of the population over the work space is considered. As an example of common multi-robots application highway traffic coordination can be mentioned. In (Pallotino et al., 2007) is presented decentralized approach using traffic rules for control of tens vehicles. The method enables dynamically adding and removing of the vehicles and is based only on local communication which makes the algorithm scalable. Algorithms designed for smaller groups of robots are usually aimed at maintaining of vehicles in a predefined formation for the purpose of cooperative tasks accomplishing (as can be e.g. box pushing (Vig & Adams, 2006), load carrying (Tanner et al., 2003), snow shoveling (Saska et al., 2008) or aircraft as well as satellites cooperative mapping (Ren & Beard, 2003; Kang & Sparks, 2000). Another interesting application of formation driving is presented in (Fahimi, 2007) where autonomous boats are maintained in formations under sliding mode, which provides faster movement. The hot research topics in formations of autonomous robots, investigated nowadays, include e.g. data fusion: (Kaminka et al., 2008) represents the sensing capabilities using a monitoring multigraph. This approach allows the robots to adjust to sensory failures by switching of control graphs on-line. An application of data fusion can be cooperative localization of mobile formations: (Mourikis & Roumeliotis |
