A low cost localization algorithm for an autonomous lawnmower

Abstract

This paper aims at implementing a localization algorithm, based on two cascaded Kalman filters, in order to localize an autonomous lawnmower which operates in an outdoor environment using only low cost sensors. In particular the position and the orientation of the robot are estimated using a three axis Gyroscope, an RFID (Radio Frequency IDentification) antenna and an RFID reader (which reads the presence of RFID tags scattered on the border of the lawn to be mowed) and an RF (Radio Frequency) antenna, on-board the robot, which measures the RSSI (Received Signal Strength Indicator) of the signal sent by other RF end devices positioned in the working area in known positions. The efficiency of the proposed algorithm is then tested first through simulations and then experimentally on a prototype lawnmower.