Title :
Improving the Robustness Properties of Robot Localization Procedures with Respect to Environment Features Uncertainties
Author :
Ippoliti, G. ; Jetto, L. ; la Manna, A. ; Longhi, S.
Author_Institution :
Dipartimento di Ingegneria Informatica, Gestionale e dell’Automazione Università Politecnica delle Marche Via Brecce Bianche, 60131 Ancona, Italy g.ippoliti@diiga.univpm.it
Abstract :
In this paper the localization and environment feature estimation problems are formulated in a stochastic setting and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, gyroscope and sonar measures. As gyroscopic measures are much more reliable than the other ones, the localization algorithm gives rise to a nearly singular EKF. This problem is dealt with defining a lower order non singular EKF.
Keywords :
Kalman filtering; Localization; Mobile robots; Equations; Filtering; Mobile robots; Robot kinematics; Robot localization; Robustness; Stochastic processes; Uncertainty; Vehicles; Wheelchairs; Kalman filtering; Localization; Mobile robots;
Conference_Titel :
Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on
Print_ISBN :
0-7803-8914-X
DOI :
10.1109/ROBOT.2005.1570319
