Decentralized control strategies for multirobot systems have been extensively studied over the past few years. Typically, these strategies aim at exploiting local interaction rules to regulate the overall state of the multirobot system toward a desired configuration, thus generating some desired coordinated behaviors, such as synchronization, swarming, deployment, or formation control. However, when considering the real-world application of multirobot systems, more complex cooperative dynamic behaviors are desirable. Along these lines, in this paper, we propose a methodology to control a multirobot system for cooperatively tracking arbitrarily defined periodic setpoint trajectories. This objective is fulfilled partitioning the multirobot system into independent robots (that can provide control inputs) and dependent robots (that are controlled through local interaction). The motion of the independent robots is then defined in such a way that, exploiting local interactions, the dependent robots are controlled to track the desired trajectories. The proposed control strategy is validated by means of simulations and experiments on real robots.

Decentralized control of networked systems has been widely investigated in the literature, with the aim of regulating the overall state of the system to some desired configuration, thus obtaining coordinated emerging behaviors (e.g. synchronization, swarming, coverage, formation control) by means of local interaction. In this paper we introduce a methodology to solve a tracking problem, that is defining a decentralized control strategy for making a networked system follow an arbitrarily defined periodic setpoint function. The most suitable interconnection topology is defined together with the control law as the solution of a constrained optimization problem, in order to ensure asymptotic tracking. Simulations are provided for validating the proposed control strategy.

Decentralized control of networked systems has been widely investigated in the literature, with the aim of obtaining coordinated emerging behaviors (e.g. synchronization, swarming, coverage, formation control) by means of local interaction. In this paper we consider the possibility of injecting external inputs into the networked system, in order to obtain more complex cooperative behaviors. Specifically, we introduce a strategy that makes it possible to control the overall state of the networked system by directly controlling only a subset of the networked agents, namely the leaders. Exploiting local interaction rules, it is possible to define the inputs for the leaders in such a way that each follower is forced to track a desired periodic setpoint.