In this paper the robust robot localization problem with respect to uncertainties on environment features is formulated in a stochastic setting, and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, gyroscopic, and sonar measures. As gyroscopic readings are much more reliable than the other ones, the localization algorithm gives rise to a nearly singular EKF. This problem is dealt with by defining a reduced order nonsingular EKF. The robust solution has been implemented and tested on a powered wheelchair.
Robust robot localization by sensors with different degree of accuracy / Ippoliti, Gianluca; La Manna, Alessia; Longhi, Sauro. - In: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS. - ISSN 0921-0296. - 56:3(2009), pp. 259-276. [10.1007/s10846-009-9311-4]
Robust robot localization by sensors with different degree of accuracy
IPPOLITI, Gianluca;LONGHI, SAURO
2009-01-01
Abstract
In this paper the robust robot localization problem with respect to uncertainties on environment features is formulated in a stochastic setting, and an Extended Kalman Filtering (EKF) approach is proposed for the integration of odometric, gyroscopic, and sonar measures. As gyroscopic readings are much more reliable than the other ones, the localization algorithm gives rise to a nearly singular EKF. This problem is dealt with by defining a reduced order nonsingular EKF. The robust solution has been implemented and tested on a powered wheelchair.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
