Economical implementation of control loops for multi-robot systems

Abstract

In spite of the multiple advantages that multi-robot systems offer, to turn them into a realistic option and to get their proliferation, they must be economically attractive. Multi-robot systems are composed of several robots that generally are similar, so if an economic optimization is done in one of them, such optimization can be replicated in each member. In this paper we deal with the economic optimization of each control loops of the subsystems that each robot must control individually. As the subsystems can be complex, we propose to use a Predictive Control modeled by Time Delayed Neural Networks and implemented using very low cost Field Programmable Gate Arrays. © 2009 Springer Berlin Heidelberg.