Hardware and Software Co-design for the EKF Applied to the Mobile Robotics Localization Problem

Abstract

This paper describes a Hardware/Software Co-design approach for the Extended Kalman Filter (EKF) applied to the localization problem in mobile robotics. The EKF algorithm has been implemented and run on an Altera Cyclone IV FPGA with a Nios II embedded processor jointly with specific hardware modules, being adapted and applied to the mobile platform Pioneer 3AT (P3AT). In order to achieve this, we developed both the model of the mobile robot and its measurement systems previously to obtain the respective EKF equations. In the prediction step of the EKF algorithm, a system model based on concepts of dead-reckoning has been used and its implementation was achieved in software, using the Nios II processor. Conversely, in the estimation step of the EKF algorithm the respective equations have been implemented directly in hardware, producing an overall balanced implementation.