Title :
Sensor integration for mobile robot position determination
Author :
Azizi, F. ; Houshangi, Nasser
Author_Institution :
Dept. of Eng., Purdue Univ. Calumet, Hammond, IN, USA
Abstract :
The objective of the work presented is to determine an accurate position and orientation for mobile robots based on information received from multiple sensors. The approach taken in this paper is to integrate the information from odometry with the inertial system using Unscented Kalman Filter (UKF). The UKF is the newest extension of widely used estimation method, Kalman Filter. The UKF is more accurate and simpler than the extended Kalman filter applied to nonlinear systems.
Keywords :
Kalman filters; distance measurement; inertial systems; mobile robots; nonlinear systems; sensor fusion; UKF; Unscented Kalman Filter; inertial system; mobile robot position determination; multiple sensors; nonlinear systems; odometry; orientation determination; sensor integration; Accelerometers; Gyroscopes; Mobile robots; Nonlinear optics; Nonlinear systems; Optical filters; Optical sensors; Robot sensing systems; Vehicles; Wheels;
Conference_Titel :
Systems, Man and Cybernetics, 2003. IEEE International Conference on
Print_ISBN :
0-7803-7952-7
DOI :
10.1109/ICSMC.2003.1244564
