This dissertation focuses on distributed agreement strategies for multi-robot systems. First of all, we deal with consensus algorithms for heterogeneous systems, representing, for example, different models or generations of robots. In the sequel, we propose two solutions to improve the connectivity properties of the system. Firstly, we show how to improve the consensus algorithm's convergence rate by modifying the classical control algorithms. More precisely, we apply the stabilizing delay principle and we show how appropriately sampled information can be used in the controller's design. Finally, we design and analyse an algorithm for the compact deployment of agents. In this approach, that increases the number of connections of the graph, the desired configuration of the swarm is entirely specified by the inter-agent angles. The proposed strategy is a completely distributed algorithm, only based on local information that allows swarm's self-organization.
