Boston University’s Mac Schwager presents “Multi-Robot Systems for Monitoring and Controlling Large Scale Environments” as part of the IRIM Robotics Seminar Series. The event will be held in the TSRB Banquet Hall from 12-1 p.m. and is open to the public.

Abstract

Groups of aerial, ground, and sea robots working collaboratively have the potential to transform the way we sense and interact with our environment at large scales. They can serve as eyes-in-the-sky for environmental scientists, farmers, and law enforcement agencies, providing critical, real-time information about dynamic environments and cityscapes. They can even help us to control large-scale environmental processes, autonomously cleaning up oil spills, tending to the needs of crop lands, and fighting forest fires, while humans stay at a safe distance. This talk will present an overview of research toward the realization of this vision, giving special attention to recent work on distributed optimization-based control algorithms for groups of aerial robots to monitor large-scale environments. I will describe a general optimization-based control design methodology for synthesizing practical, distributed robot controllers with provable stability and convergence properties. I will also describe low-level control techniques based on differential flatness to coordinate the motion of teams of multirotor helicopters in an agile and computationally efficient manner. Experimental studies with groups of multirotor robots flying both outdoors and indoors using these controllers will also be discussed.

Bio

Mac Schwager is an assistant professor in the Department of Mechanical Engineering and the Division of Systems Engineering at Boston University. He obtained his BS degree in 2000 from Stanford University, his MS degree from MIT in 2005, and his PhD degree from MIT in 2009. He was a postdoctoral researcher working jointly in the GRASP lab at the University of Pennsylvania and CSAIL at MIT from 2010 to 2012. Schwager's research interests are in distributed algorithms for control, perception, and learning in groups of robots and animals. He received the NSF CAREER award in 2014.