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...
This paper addresses the connectedness issue in multiagent coordination, i.e., the problem of ensuring that a group of mobile agents stays connected while achieving some performance objective. In particular, we study the rendezvous and the formation control problems over dynamic interaction graphs, and by adding appropriate weights to the edges in the graphs, we guarantee that the graphs stay connected.  To accomplish cooperative tasks, robotic systems are often required to communicate with each other. Thus, maintaining connectivity of the interagent communication graph is a fundamental issue in the field of multi-robot systems. In this paper we present a completely decentralized control strategy for global connectivity maintenance of the interagent communication graph. We describe a gradient-based control strategy that exploits decentralized estimation of the algebraic connectivity. The proposed control algorithm guarantees the global connectivity of the communication graph without requiring maintenance of the local connectivity between the robotic systems. The control strategy is validated by means of an analytical proof and simulative results. In order to accomplish cooperative tasks, multi-robot systems are required to communicate among each other. Thus, maintaining the connectivity of the communication graph is a fundamental issue. Connectivity maintenance has been extensively studied in the last few years, but generally considering only kinematic agents. In this paper we will introduce a control strategy that, exploiting a decentralized procedure for the estimation of the algebraic connectivity of the graph, ensures the connectivity maintenance for groups of Lagrangian systems. The control strategy is validated by means of analytical proofs and simulation results.  In this paper, we provide a theoretical framework for controlling graph connectivity in mobile robot networks. We discuss proximity-based communication models composed of disk-based or uniformly-fading-signal-strength communication links. A graph-theoretic definition of connectivity is provided, as well as an equivalent definition based on algebraic graph theory, which employs the adjacency and Laplacian matrices of the graph and their spectral properties. Based on these results, we discuss centralized and distributed algorithms to maintain, increase, and control connectivity in mobile robot networks. The various approaches discussed in this paper range from convex optimization and subgradient-descent algorithms, for the maximization of the algebraic connectivity of the network, to potential fields and hybrid systems that maintain communication links or control the network topology in a least restrictive manner. Common to these approaches is the use of mobility to control the topology of the underlying communication network. We discuss applications of connectivity control to multirobot rendezvous, flocking and formation control, where so far, network connectivity has been considered an assumption.