In multiagent surveillance missions, a group of agents monitors some points of interest to provide situational awareness. For agents with local communication capabilities, one way to transmit the surveillance information to a base is streaming by the instantaneous data via multihop communications over a connected network. However, a connected communication network may become disconnected if some agents leave the surveillance area (for example, for refueling). This paper presents a locally applicable, efficient, and scalable strategy that guarantees a connected communication network between the base and the agents in the face of any agent removal. The proposed decentralized strategy is based on a sequence of local replacements, which are initiated by the agent leaving the network. It is shown that the replacement sequence always ends with the relocation of an agent, for which the absence from its current position does not disconnect the network. Furthermore, the optimality (that is, the minimum number of r...
Recently, a great amount of interest has been devoted to the analysis of multi-agent systems via the graph theory. In these studies, the of a graph represent the agents (such as robots, sensors or individuals), and represent the direct interactions between them. For such a representation, a fundamental graph property related to the system robustness is graph connectivity (e.g. @cite_30 @cite_31 @cite_38 and the literature cited within). As such, the robustness of a system is related to the total number of edges nodes, whose removal will cause a network disconnection. For the graph theoretical connectivity control of mobile systems against edge failure, the literature is including, but not limited to, optimization based connectivity control (e.g. @cite_10 ), continuous feedback connectivity control (e.g. @cite_6 ), and control based on the estimation of the algebraic connectivity (e.g. @cite_3 ). In these studies, the authors mainly consider uncertainty in edges and assume a constant number of nodes.
@cite_30 @cite_38 @cite_6 @cite_3 @cite_31 @cite_10
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In this paper, we address the problem of agent loss in vehicle formations and sensor networks via two separate approaches: (1) perform a ‘self-repair’ operation in the event of agent loss to recover desirable information architecture properties or (2) introduce robustness into the information architecture a priori such that agent loss does not destroy desirable properties. We model the information architecture as a graph G(V, E), where V is a set of vertices representing the agents and E is a set of edges representing information flow amongst the agents. We focus on two properties of the graph called rigidity and global rigidity, which are required for formation shape maintenance and sensor network self-localization, respectively. For the self-repair approach, we show that while previous results permit local repair involving only neighbours of the lost agent, the repair cannot always be implemented using only local information. We present new results that can be applied to make the local repair using only local information. We describe implementation and illustrate with algorithms and examples. For the robustness approach, we investigate the structure of graphs with the property that rigidity or global rigidity is preserved after removing any single vertex (we call the property as 2-vertex-rigidity or 2-vertex-global-rigidity, respectively). Information architectures with such properties would allow formation shape maintenance or self-localization to be performed even in the event of agent failure. We review a characterization of a class of 2-vertex-rigidity and develop a separate class, making significant strides towards a complete characterization. We also present a characterization of a class of 2-vertex-global-rigidity. Copyright © 2008 John Wiley & Sons, Ltd. Connectivity is a fundamental property in many networked systems for communication and coordination among the agents. Removal of any agent from a network may destroy its connectivity. In order to maintain the connectivity of mobile networked systems in agent loss, one can design a robust network topology such that the network is tolerant to a finite number of agent losses, and or develop a control strategy, such that the network reconfigures itself until the connectivity requirements are satisfied. In this paper, we introduce a decentralized control scheme based on a sequence of replacements, each of which occurs between an agent and one of its neighbors. The proposed scheme always maintains the graph connectivity, and it does not rely on any gathering of global information either a priori or at the intermediate steps of a mission. Moreover, the proposed scheme does not cause any increase in the total number of edges and the maximum node degree in a graph, thus it assures no increase in the overall communication cost due to the topological changes. In this study, we validate the control strategy by means of an analytical proof and simulation results. A distributed control law that guarantees connectivity maintenance in a network of multiple mobile agents is presented. The control law, which lets the agents perform formation manoeuvres, respects sensor limitations by allowing each agent to only take into account agents within its sensing radius. In contrast to previous approaches to the problem, the proposed control law does not attain infinite values whenever an edge of the communication graph tends to be lost. This is achieved via the use of decentralised navigation functions, which are bounded potential fields. The navigation functions are defined to take into account the connectivity maintenance objective. The authors first treat the case of connectivity maintenance for a static communication graph and then extend the result to the case of dynamic graphs. The results are illustrated on a formation control problem. Control of mobile networks raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In particular, in applications involving mobile sensor networks and multi-agent systems, a great new challenge is the development of distributed motion algorithms that guarantee connectivity of the overall network. In this paper, we address this challenge using a novel control decomposition. First, motion control is performed in the continuous state space, where nearest neighbor potential fields are used to maintain existing links in the network. Second, distributed coordination protocols in the discrete graph space ensure connectivity of the switching network topology. Coordination is based on locally updated estimates of the abstract network topology by every agent as well as distributed auctions that enable tie breaking whenever simultaneous link deletions may violate connectivity. Integration of the overall system results in a distributed, multi- agent, hybrid system for which we show that, under certain secondary objectives on the agents and the assumption that the initial network is connected, the resulting motion always satisfies connectivity of the network. Our approach can also account for communication time delays in the network as well as collision avoidance, while its efficiency and scalability properties are illustrated in nontrivial computer simulations.