Multi-Robot Systems Control Implementation

Abstract

This paper has started thinking about the convenience that the computational capacity of robots that belong to multi-robot systems was devoted exclusively to high level functions they have to perform due to being a member of such system. However, each robot must have so many internal control loops as subsystems, and in some cases they aren’t controllable through classic techniques. In these cases, predictive control is a good option because it can deal with subsystems that classical PID controllers can't, but it’s computationally expensive. In this paper it has been shown how the predictive controllers can be modeled using Time Delayed Neural Networks, which implementation is very cheap using very low cost FPGAs. This way we can reduce de price of each member of multi-robot system, because the investment in computational capacity must cover only the high level functions, ignoring the subsystems that it had, which are solved with very low cost FPGAs.