Ultrasonic localization and pose tracking of an autonomous mobile robot via fuzzy adaptive extended information filtering

Abstract

This paper presents methodologies and technologies for ultrasonic localization and pose tracking of an autonomous mobile robot (AMR) by using a fuzzy adaptive extended information filtering (FAEIF) scheme. A novel ultrasonic localization system, which consists of two ultrasonic transmitters and three receivers, is proposed to estimate both the static and the dynamic position and orientation of the AMR. FAEIF is presented to improve estimation accuracy and robustness for the proposed localization system, while the system lacks sufficient information of complete models or the process and measurement noise varies with time. Static pose estimation that utilizes the averaging approach is also investigated. Six time-of-flight ultrasonic measurements, together with the vehicle's dead-reckoned localization information, are merged to update the vehicle's pose by utilizing the FAEIF sensor fusion algorithm. The proposed algorithms were implemented using an industrial personal computer with a computation speed of 800 MHz and standard C++ programming techniques. The system prototype, together with computer simulations and experimental results, was used to confirm that the system not only provides precise estimation of both the static and dynamic pose of the AMR but also provides a simple economical structure for navigational use and installation/calibration.