Robotics, Aerospace and Information Networks (RAIN)

In recent years, network science has emerged as a powerful conceptual paradigm in science and engineering. Constructs and phenomena such as random graphs, small-world networks, and phase transition now appear in a wide variety of research works, ranging from social networks, statistical physics, sensor networks, and, of course, multi-agent coordination and control.

The reason for this unprecedented attention to network science is twofold. On one hand, in a number of disciplines -- particularly in biological and material sciences -- it has become vital to gain a deeper understanding of the role that inter-elemental interactions play in the collective functionality of multi-layered systems. On the other hand, technological advances have facilitated an ability to synthesize networked engineering systems -- such as those found in multi-vehicle systems, sensor networks, and nano-structures -- that resemble their natural counterparts in terms of their functional and operational complexity.

A basic scientific premise in network science is that the structure of the network, when abstracted for example in terms of a graph, influences the dynamical properties exhibited at the system level. In this avenue, one might examine -- for example -- the relationship between higher levels of connectivity in the network and the convergence rate to certain system equilibria or limit cycle. The focus of our research group is on dynamics and control of networked systems with particular attention to their aerospace engineering applications.

Example: Distributed Aerospace Systems

Future aerospace missions are being developed that will focus on autonomous distributed multi-vehicle systems on ground, in space and air. A distributed multi-vehicle system is a collection of physically separated entities whose states are coordinated to achieve a local or global objective. Multiple spacecraft formation flying is one of the prime examples of such distributed systems. Well known examples of formations in nature are fish swimming in a school or birds flying in a V. Humans move in formations too, whether we are marching in a parade or dancing in a group.

Why study distributed space systems?

Recently, these self-coordinating distributed systems have been identified as the enabling technology for many future NASA, Air Force, Navy, and civilian space missions. By altering the configuration of these distributed systems, a wider variety of missions can be accomplished as compared with the equivalent single, large, and often highly flexible structures. As compared with its monolithic counterpart, the distributed system architecture promises a modular design paradigm for aerospace systems while leading to significant cost reduction in design, manufacturing, and  operation of many future aerospace systems.

Technical focus of the group

The research of our group is faceted, with a blend of theory, computation, and experimentation.

The key areas of interest currently include:
  1. Theoretical underpinnings of networked systems from a control-theoretic perspective, including performance, graph- theoretic methods, randomness, robustness and security.
  2. Guidance, navigation, estimation, and control for single and multiple spacecraft systems.
  3. Applications of networked systems and control in multi- platform aerial (quadrotors, balloons, helicopters) and ground systems, biology, nano-systems, quantum networks, particularly pertaining to their estimation and control.
  4. Optimization and control applications in engineering systems, such as total energy optimization in aerospace systems, clean energy, and smart grids.
  5. Control and optimization theory and algorithms in a broad sense.