LCSR Seminar: Yancy Diaz-Mercado

Description

Yancy Diaz-Mercado, assistant professor in the Department of Mechanical Engineering at the University of Maryland, College Park, will give a talk titled "Strength in Numbers: Leveraging Coordination for Guaranteed Performance in Multi-Robot Systems" for the Laboratory for Computational Sensing + Robotics.

Diaz-Mercado is also the director of the Collaborative Controls and Robotics Laboratory, whose research focus is on developing collaborative autonomy for multi-agent systems, robotics, magnetic manipulation, and enabling human-swarm interactions. Before joining the faculty at the University of Maryland, College Park in 2018, Diaz was a senior professional engineer with the Johns Hopkins University Applied Physics Laboratory, where he was a member of the advanced concepts section within the guidance, navigation, and controls group in the air and missile defense sector.

Abstract:

As technology continues to improve and powerful computing becomes more easily accessible and interconnected, we will continue to see the emergence of multi-agent and networked systems impacting real world problems as with Amazon Robotics automated warehouses and delivery drone projects, and as envisioned by Japan's Society 5.0 plan. At the Collaborative Controls and Robotics Laboratory, we use control theory and machine learning to model and control network control systems, and develop scalable, distributed coordination approaches that guarantee the performance of the multi-robot system for effective deployment. During the first part of this talk, I will present our work on distributed resource allocation for human-robot swarm teaming. Using the framework of coverage control, we demonstrate that a collection of robots is able to optimally distribute over a time-varying domain on the fly while only relying on local information, facilitating the ability of an operator to single handedly shape and control a large collection of robots. During the second part, we show that, through coordination, a collection of kinematically inferior agents can work together to always win against a superior player in reach-avoid games.