Multi-robot teams composed of ground and aerial vehicles have gained attention during the last few years. We present a scenario where both types of robots must monitor the same area from different view points. In this paper, we propose two Lloyd-based tracking strategies to allow the ground robots (agents) to follow the aerial ones (targets), keeping the connectivity between the agents. The first strategy establishes density functions on the environment so that the targets acquire more importance than other zones, while the second one iteratively modifies the virtual limits of the working area depending on the positions of the targets. We consider the connectivity maintenance due to the fact that coverage tasks tend to spread the agents as much as possible, which is addressed by restricting their motions so that they keep the links of a minimum spanning tree of the communication graph. We provide a thorough parametric study of the performance of the proposed strategies under several simulated scenarios. In addition, the methods are implemented and tested using realistic robotic simulation environments and real experiments.
A limitation of some multi-robot strategies is that often there are no guarantees that the network will remain connected as the agents operate. This is an important issue, since robots often must be able to exchange data and communicate with each other in order to coordinate and to successfully fulfill their tasks. In @cite_1 this term is included in the control law governing the global coordination objective. It keeps an accurate estimate of the time-varying Fiedler eigenvector. Depending on the high-level coordination strategy, the connectivity control term will affect its achievement. It is remarkable that they study both theoretically and experimentally these effects. In @cite_0 there is a control law that enforces connectivity, and an additional bounded control term, that encapsulates the high-level control law for multi-robot cooperation. In addition, they design a control law that guarantees that the trajectories of the agents remain within a domain. This is done by means of a repulsion vector nearby the boundaries of the domain. A review of other connectivity control methods can be found in @cite_12 . All these control methods often rely on keeping up to date estimates of data that encapsulates global properties.
@cite_0 @cite_1 @cite_12
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In this paper, we address the connectivity maintenance problem for a multirobot system that moves according to a given bounded collective control objective. We assume that the interaction among the robotic units is limited by a given visibility radius both in terms of sensing and communication capabilities. For this scenario, we propose a decentralized bounded control law that can provably preserve the connectivity of the multirobot system over time. We characterize the effect of the connectivity control term on the achievement of the collective control objective by resorting to an input-to-state stability-like analysis. We provide numerical and experimental results to corroborate the theoretical findings and assess the effectiveness of the proposed bounded connectivity maintenance control law. 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. To accomplish cooperative tasks, robotic systems are often required to communicate with each other. Thus, maintaining connectivity of the 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 communication graph. Considering the disk communication model, we describe a gradient-based control strategy that exploits decentralized estimation of the algebraic connectivity. Unlike previous approaches available in the literature, the proposed control algorithm solves the global connectivity problem in a decentralized manner providing theoretical guarantees, without requiring maintenance of the local connectivity between robotic systems. Moreover, results obtained with simulations and experiments on real robots are described for demonstrating the efficacy of the proposed algorithm. 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.