Design of efficient, intelligent, and safe multi-agent cyber-physical systems is challenging, especially as onboard resources are stretched to maximize performance. Computation, communication, and control resources must be carefully allocated to achieve mission objectives. Traditionally, this allocation is fixed and designed for worst-case anticipated conditions despite the dynamic environment in which it operates. But intelligent CPS should be capable of adjusting resources to respond to a dynamic environment and changing mission objectives. This requires control, machine learning, planning, and other autonomy algorithms that achieve different quality of service levels when resources are reallocated. In this talk I will discuss how this can be achieved in single, and multi-agent control systems, using a multi-agent multicopter scenario as an example application. Results show that similar performance, but drastically improved resource allocation can be achieved through coupled co-design of algorithms.
Justin M. Bradley holds a B.S. in computer engineering (2005) and M.S. in electrical engineering (2007) from Brigham Young University, and M.S. (2012) and Ph.D. (2014) degrees in aerospace engineering from the University of Michigan. He worked at Lawrence Livermore National Lab as a control software engineer on the Integrated Computer Control System for the National Ignition Facility. He is currently an assistant professor in the Department of Computer Science and Engineering at the University of Nebraska-Lincoln and a co-director of the Nebraska Intelligent MoBile Unmanned Systems (NIMBUS) lab. He conducts research in cyber-physical systems with an emphasis on decision and control, control software, and robot autonomy in aerospace systems.