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

Abstract

This paper develops methodologies and technologies for ultrasonic self-localization of an autonomous mobile robot (AMR) using a fuzzy adaptive extended information filtering scheme. A novel ultrasonic localization system consisting of two ultrasonic transmitters and three receivers, is presented to estimate both the static and dynamic position and orientation of the AMR. A fuzzy adaptive extended information filter (FAEIF) is presented to improve estimation accuracy and robustness for the proposed localization system, while the system lacks of sufficient information of complete models of the process and measurement noise varies with time. A static pose estimation utilizing the averaging approach is investigated as well. Six time-of-flight ultrasonic measurements together with the vehicle's dead-reckoned location information are merged to update the vehicle's dead-reckoned location information are merged to update the vehicle's pose by utilizing FAEIF sensor fusion algorithm. The proposed algorithm 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 has been 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 simpler and more economical structure for navigation use and installation/calibration.