A fuzzy logic approach in feature based robot navigation using interval analysis and UKF

Abstract

Multiple sensor fusion for robot localisation and navigation has attracted a lot of interest in recent years. This paper describes a sensor based navigation approach using an interval analysis (IA) based adaptive mechanism for an unscented Kalman filter (UKF). The robot is equipped with inertial sensors (INS), encoders and ultrasonic sensors. An UKF is used to estimate the robot position using the inertial sensors and encoders. Since the UKF estimates may be affected by bias, drift etc., an adaptive mechanism using IA to correct these defects in estimates is proposed. The IA robot position estimate may be conservative, in which case multiple measurements are taken and the multiple interval robot position is fused together using fuzzy logic to obtain a single interval robot position estimate. In the presence of landmarks the complementary robot position information from the IA algorithm using ultrasonic sensors is used to estimate and bound the errors in the UKF robot position estimate.