Real-Time Uncertainty Estimation of Odometric Trajectory as a Function of the Actual Manoeuvres of Autonomous Guided Vehicles

Author

De Cecco, Mariolino ; Baglivo, Luca ; Pertile, Marco

Author_Institution

Dept. of Struct. Mech. Eng., Trento Univ.

fYear

2006

fDate

20-21 April 2006

Firstpage

80

Lastpage

85

Abstract

This paper presents the description of a novel uncertainty estimation method employed for the navigation of autonomous guided vehicles. In the proposed algorithm the uncertainty of the odometric navigation system is estimated as a function of the actual manoeuvre being carried out, which is identified by navigation data itself. The result is a recursive method for estimating the evolution of spatial uncertainty which takes into account the unknown systematic effects. The method is explained starting from the measurement models and its parameters as a function of the actual manoeuvres. Experimental verification was carried out using an autonomous vehicle. Compatibility between a reference environment referred system and the uncertainty estimated by the proposed method was achieved 95% of the trials

Keywords

Monte Carlo methods; distance measurement; measurement uncertainty; navigation; recursive estimation; remotely operated vehicles; Monte Carlo simulation; autonomous guided vehicles; odometric navigation system; odometric trajectory; pose estimation; real-time uncertainty estimation; recursive method; spatial covariance; Kinematics; Mechanical engineering; Mobile robots; Navigation; Path planning; Position measurement; Recursive estimation; Remotely operated vehicles; Uncertain systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Methods for Uncertainty Estimation in Measurement, 2006. AMUEM 2006. Proceedings of the 2006 IEEE International Workshop on

Conference_Location

Sardagna

Print_ISBN

1-4244-0249-2

Type

conf

DOI

10.1109/AMYEM.2006.1650755

Filename

1650755