Abstract
This paper addresses a distributed connectivity control problem in networked multi-agent systems. The system communication topology is controlled through the algebraic connectivity measure, the second smallest eigenvalue of the communication graph Laplacian. The algebraic connectivity is estimated locally in a decentralized manner through a trust-based consensus algorithm, in which the agents communicate the perceived quality of the communication links in the system with their set of neighbors. In the presented approach, link qualities represent the weights of the communication graph from which the adjacency matrix is estimated. The Laplacian matrix and its eigenvalues, including the algebraic connectivity, are then calculated from this local estimate of the global adjacency matrix. A method for network topology control is proposed, which creates and deletes communication links based on the Albert-Barabási probabilistic model, depending on the estimated and referenced connectivity level. The proposed algebraic connectivity estimation and connectivity maintenance strategy have been validated both in simulation and on a physical robot swarm, demonstrating the method performance under varying initial topology of the communication graph, different multi-agent system sizes, in various deployment scenarios, and in the case of agent failure.
Highlights
A large research interest in the field of multi-agent systems, exploiting the scalability, robustness, and efficiency of such systems, is not surprising
Compared to power iteration methods for distributed estimation of the algebraic connectivity, that have been intensively investigated in the decentralized multi-agent systems [18]–[22], as described in Section I-A, our method provides the same complexity level with the benefit of estimating the entire graph’s topology in a decentralized manner
To demonstrate the effectiveness of the proposed consensus-based method for calculation of λ2 and the described control law for connectivity maintenance, we conducted extensive simulations for three different group sizes, i.e. we have chosen a group of 5, 9, and 25 robots. For each of these examples, we generated an initial communication graph topology in order to set the initial distribution of robots
Summary
A large research interest in the field of multi-agent systems, exploiting the scalability, robustness, and efficiency of such systems, is not surprising. Bogdan are with LARICS Laboratory for Robotics and Intelligent Control Systems, University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, Zagreb 10000, Croatia (marsela.polic, marko.krizmancic, stjepan.bogdan) at fer.hr. A broad information exchange requires increasing the number of communication links, which can lead to deteriorated control, for example in case of delays due to token exchange. Graph theory mathematical formalism can be used to provide insights into the global properties of the underlying network topology, an approach exploited in this work. This enables adaptation of the system communication topology to retain the desired functionality even under disturbances
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
