Granular stochastic modeling of robot micrometric precision

Author

Brethé, Jean-François

Author_Institution

Groupe de Rech. en Electrotech. et Autom. du Havre, Univ. of LE HAVRE, Le Havre, France

fYear

2011

fDate

25-30 Sept. 2011

Firstpage

4066

Lastpage

4071

Abstract

The paper aims at modeling and quantifying robot precision when it is possible to obtain information from external sensors in the operating area. The author proves that in this situation, neither the pose repeatability, nor the pose accuracy are adequate to calculate the maximum position error. A new paradigm is then proposed: granulous space modeling which combines spatial resolution and actuators´ repeatability. This stochastic modeling is first detailed in unidimensional space then in the case of bidimensional space. The methodology to compute the maximal position error is given and compared with other approaches.

Keywords

position control; robots; actuator repeatability; bidimensional space; granular stochastic modeling; granulous space modeling; maximal position error; maximum position error; pose accuracy; quantifying robot precision; robot micrometric precision; spatial resolution; unidimensional space; Accuracy; Aerospace electronics; Computational modeling; Robot kinematics; Spatial resolution; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on

Conference_Location

San Francisco, CA

ISSN

2153-0858

Print_ISBN

978-1-61284-454-1

Type

conf

DOI

10.1109/IROS.2011.6094536

Filename

6094536