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

This paper presents an improved global localization method and an improved pose tracking approach for an indoor autonomous mobile robot (AMR) with ultrasonic and laser scanning measurements using a fuzzy extended information filtering scheme. An ultrasonic self-localization system, consisting of two ultrasonic transmitters and three receivers, is presented to estimate both the unknown global position and orientation of the AMR in a world frame, and a fuzzy adaptive extended information filter (FAEIF) is proposed to improve estimation accuracy for the ultrasonic localization system. With the odometric data from the driving wheels and the laser scanning measurements from the robot's surrounding, a FAEIF-based pose tracking algorithm is proposed to continuously keep track of the robot's poses at slow speeds less than 100 cm/sec. The proposed algorithms were implemented using an industrial personal computer with a computation speed of 800MHz, and standard C++ programming techniques. The system prototype together with experimental results has been used to confirm the merit of the proposed methods in comparison with the well-known EIF