Efficient collaboration for mobile robotic networks in dynamic environments

Abstract: In this talk, we will address the following class of multi-agent problems. Consider a geographical region, in which a certain stochastic process generates spatially localized "tasks." Tasks can represent, for example, pick- up and/or delivery of goods, data packets generated by mobile user terminals, or on-site investigation of events of interest. In a biological setting, a taks might represent the availability of a food
item, or other scarce resource. A number of mobile agents are able to complete these task by moving to the corresponding location. It is desired to minimize the average delay in task completion, or some other measure of quality of service.

The underlying mathematical problem in many of these applications can be studied within the framework of spatial queues, in which service the tasks as customers and the mobile agents as servers. Cooperation between agents occurs as workload sharing. Control policies have to typically address two key challenges: task allocation among the agents and service schedule for each agent. In general, these two features are highly coupled and, therefore, devising an optimal or, at least, a provably efficient policy is an extremely difficult problem. Considering motion constraints for the agents, as should be done for Unmanned Aerial Vehicles (UAVs), complicates things further.

A natural way to reduce the complexity is to partition the workspace among the agents and then let each agent follow a certain set of rules in its own region. To which extent does this decoupling strategy affect optimality? How can agents compute a partition of the workspace in the absence of a central authority, and with limited communication  abilities? We will consider a number of scenarios, in which different partitions arise in optimal policies. In addition, we will illustrate novel phase transition phenomena induced by the agents' dynamics.

Papers: Paper1, Paper2.

Biography: Emilio Frazzoli is an Associate Professor of Aeronautics and Astronautics with the Laboratory for Information and Decision Systems at the Massachusetts Institute of Technology . He received a Laurea degree in Aerospace Engineering from the University of Rome, "Sapienza" , Italy, in 1994, and a Ph. D. degree in Navigation and Control Systems from the Department of Aeronautics and Astronautics of the Massachusetts Institute of Technology, in 2001. Between 1994 and 1997 he worked as an officer in the Italian Navy, and as a spacecraft dynamics specialist for the European Space Agency Operations Centre (ESOC) in Darmstadt, Germany, and Telespazio, in Rome, Italy. From 2001 to 2004 he was an Assistant Professor of Aerospace Engineering at the University of Illinois at Urbana-Champaign. From 2004 to 2006 he was an Assistant Professor of Mechanical and Aerospace Engineering at the University of California, Los Angeles. He is a Senior Member of the American Institute of Aeronautics and Astronautics and of the Institute for Electrical and Electronics Engineers. He was the recipient of a NSF CAREER award in 2002.

Dr. Frazzoli's current research interests include algorithmic, computational and geometric methods for the design of complex control systems, in aerospace and other domains. Application areas include distributed cooperative control of multiple-vehicle systems, guidance and control of agile vehicles, mobile robotics, high-confidence embedded systems.   



Emilio Frazzoli