Coping with Uncertainty in Cooperative Control for Autonomous Vehicles

 

Professor Kevin Passino

 

The Ohio State University

 

 

Abstract: Groups of autonomous vehicles that coordinate their actions via inter-vehicle communications sometimes have the ability to perform tasks more efficiently than individual vehicles that lack any communication capabilities. The uncertainty in sensing and taking actions leads to imperfections in the information on which decisions are made for cooperative or noncooperative vehicles; however, some additional uncertainty arises due to the desire for cooperation.  First, inter-vehicle communication imperfections (e.g., network delays) leads to mistakes in coordinating actions.  Second, vehicular computational constraints limit the feasible types of multi-vehicle coordination (e.g., coordinated path planning many steps into the future may not be feasible).  In this talk, cooperative control methods will be introduced that can cope with such uncertainty and hence achieve benefits over a noncooperative set of vehicles.  Applications to cooperative control for autonomous air vehicles in military missions will be used to  illustrate system level design principles and cases where uncertainty rises so high that cooperation is not beneficial.

 

Professor Passino is a IEEE Control Systems Society Distinguished Lecturer

 

 

Friday, January 16, 2004

3:30 Ð 4:30 p.m.

1500 EECS