Distributed Estimation and Control of Multi-Agent Systems
Laboratory for Intelligent Mechanical Systems
Auditorium (NSH 1305)
Refreshments 3:15 pm
Talk 3:30 pm
We are pursuing a framework for systematic design of emergent behaviors in sensing and communication networks of mobile agents. The problem is to design a control law to run on each agent, based on sensor and communication input, so that the desired collective behavior emerges. Example tasks include sensor coverage, formation control, multi-agent pursuer-evader, and other types of self-organization. The key constraints are that each agent may have significant dynamics and limited sensing, computation, motion, and communication capabilities. The behavior of the system should improve or degrade gracefully as agents are added or deleted; in other words, the approach should be scalable, robust, and require no central controller.
Our approach requires each agent to simultaneously (1) estimate properties of the global behavior of the system and (2) use those estimates in a motion control law. This suggests a systematic approach of separately designing the estimator and controller, and then ensuring that the coupled system retains desired performance properties. I will give an example applying this framework to swarm formation control, where the desired formation is described by inertial moments. Implementing a simple gradient control law on each agent, the coupled estimation and control system is globally convergent to the desired family of formations.
Kevin Lynch was a member of Carnegie Mellon's first class of
robotics Ph.D. students. After
graduation in 1996 he spent a year as a postdoctoral fellow at the AIST
Mechanical Engineering Laboratory in