The growing need for high-performance controllers in safety-critical applications like
autonomous driving motivated the development of formal safety verification techniques. In …

In multi-agent coverage control problems, agents navigate their environment to reach
locations that maximize the coverage of some density. In practice, the density is rarely …

Probabilistic swarm guidance enables autonomous microsatellites to generate their
individual trajectories independently so that the entire swarm converges to the desired …

Robots are increasingly deployed for search-and-rescue (SaR), in order to speed up
rescuing the victims in the aftermath of disasters. These robots require effective mission …

The problem of coverage control, ie, of coordinating multiple agents to optimally cover an
area, arises in various applications. However, coverage applications face two major …

As an emerging mode of urban transportation, autonomous mobility-on-demand (AMoD)
systems show the potential in improving mobility in cities through timely and door-to-door …

In cooperative multi-agent robotic systems, coordination is necessary in order to complete a
given task. Important examples include search and rescue, operations in hazardous …

Area coverage control with multi-agent systems is formulated here in the framework of
Bellman's optimality. In the literature, optimal configurations are obtained by Lloyd's …

In this article, we present a sequential distributed model predictive control (MPC) scheme for
cooperative control of multiagent systems with dynamically decoupled heterogeneous …

Abstract Model Predictive Control (MPC) can be applied to safety-critical control problems,
providing closed-loop safety and performance guarantees. Application of MPC requires …