Research Interests

The challenge of distributed control is about designing local control laws such that a desired collective behavior emerges from the local interactions between neighboring agents. The complexity of distributed control design is compensated by its undisputed benefits in terms of communication, sensing and computing power requirements, of flexibility and of robustness. Relevant problems that can be addressed using distributed control in robotic applications are the following:

• Static coverage

• Dynamic coverage/exploration/patrolling

• Navigation (flocking, formation)

• Rendezvous

• Connectivity maintenance

• Topology control

The ability to navigate their way through partially known environments in complete autonomy is a key functionality for mobile robots. However, the ambitious requirements of a new generation of robotic applications set a high bar for the development of navigation algorithms. Specifically, we can identify five classes of requirements:

• Robustness and safety in navigation

• Socially-aware motion planning

• Multi-agent coordination

• Management of highly dynamical environments

• Computation efficiency
  

A resilient multi-robot system refers to a group of robots that are designed to continue functioning even when one or more robots fail or are compromised. In other words, the system has to manage failures, disruptions, and other unexpected events. Resilience is critical in multi-robot systems because robots may encounter various challenges, such as hardware or software failures, communication disruptions or malicious attacks. These challenges can cause the robots to stop working or malfunction, which can affect the entire system's performance, reliability and even safety.