Antonio Bono

Research Abstract

Multi-Robot Systems (MRSs) have many advantages compared to single robot systems. Their redundancy and intrinsic parallelism make them more robust to failures and allow to perform complex tasks for which a single robot may not be able to. Moreover, it is much more cost-efficient to use a collaborative team of robots equipped with limited capabilities than to consider a single robot with all the required features. These qualities are the key of the current success of MRSs in many application domains such as warehousing, search-and-rescue, precision agriculture and, environmental monitoring and exploration.

However, these results come at a cost.  There are many different issues that need to be accomplished in order to manage these teams properly such as modeling and control, path planning and coordination, task allocation, and communication.

In this framework, my interests are related to control issues. I am studying math models and control systems to efficiently and safely coordinate these teams in unknown environments. In particular, I am working on discrete kinematic and dynamic models for solving problems such as consensus, flocking, tracking, and, distributed MPC to manage collision avoidance. Bio-Inspired MRSs and Swarm Intelligence/Robotics and, collaborative manipulation are other fields of investigation.