Multi-Agent Coordination by Decentralized Estimation and Control

Kevin Lynch
Mechanical Engineering Department
Northwestern University

Starting from a broad view of self-organizing systems, I will describe a framework for compiling desired collective behaviors into local control laws for groups of mobile agents. The approach is based on decentralized simultaneous estimation and control, where each agent communicates with neighbors and estimates the global performance properties needed to make intelligent local control decisions. Challenges of the approach include designing decentralized estimators that allow agents to maintain the necessary global estimates, and ensuring the stability of the complex coupled system through the use of small-gain conditions. This framework has been applied to problems in motion coordination and cooperative active sensing.

This is joint work with my student Peng Yang and my colleague Randy Freeman.

Bio:

Kevin Lynch received his Ph.D. in Robotics from Carnegie Mellon in 1996. He is currently a Charles Deering McCormick Professor of Teaching Excellence in the Mechanical Engineering Department at Northwestern University, where he is director of the Mechatronics Design Lab and co-director of the Laboratory for Intelligent Mechanical Systems. He is a co-author of ``Robot Motion Planning''(MIT Press 2005) and Senior Editor of the IEEE Transactions on Robotics. He has received the IEEE Early Academic Career Award in Robotics and Automation and Northwestern's Engineering Teacher of the Year award. His research interests include robot motion planning and control, robotic manipulation and assembly, human-robot interaction,and self-organizing systems.