Dynamic Perimeter Surveillance of Multiagent Systems: A Swarm-Based Approach.

In this article, a novel approach to generating kinematic state trajectories for single-integrator multiagent systems is developed with the aim of addressing cooperative surveillance tasks of rectangular areas. In particular, the key idea consists in driving the involved agents within a so-called containment region while simultaneously reaming outside a forbidden area around the prescribed target. As one of its main features, the proposed kinematics allows the whole multiagent configuration to rotate safely along the perimeter under both full and partial connectivity properties of the underlying topology graph. Steady-state conditions are analyzed and sufficient conditions are derived in terms of kinematic model parameters. Finally, a set of simulations is aimed at showing the capability of the kinematic descriptions to quickly buttonhole the containment region and to keep a rotating behavior around the target.

A Swarm-Based Distributed Model Predictive Control Scheme for Autonomous Vehicle Formations in Uncertain Environments.

In this article, a novel distributed model predictive control architecture is proposed for the coordination and control of multivehicle formations moving within uncertain environments. As one of its main merits, multiagent swarm modeling and leader-follower configurations are jointly exploited within an ad hoc model predictive control framework to reduce as much as possible the use of onboard sensors that is essential in long-range missions. Moreover, the feasibility and asymptotic closed-loop stability of the resulting scheme are formally proved. Finally, a laboratory experiment is used to show the effectiveness of the proposed algorithm with particular attention to the follower capability of operating in a so-called blind fashion.