Human-Computer Interaction: Ergonomics and User Interfaces - Vol. 1

By Hans-Jörg Bullinger; Jürgen Ziegler | Go to book overview

Use of Fuzzy Logic in an Adaptive Interface
meant for Teleoperation

Fabrice Vienne[1][2], Anne-Marie Jolly-Desodt[2], Daniel Jolly[2] [1] Ecole des Hautes Etudes Industrielles, Groupe de recherche E.R.A.S.M., 13 rue de Toul 59046 Lille Cedex, France E-mail:fabrice.vienne@hei.fr [2] Laboratoire dAutomatique I3D, Bat P2, Universitä des Sciences et Technologies de Lille - 59655 Villeneuve d'Ascq Cedex, France E-mail: {Anne-Marie.Desodt, Daniel.Jolly}@univ-lillel.fr


1
Introduction

A teleoperation system is mainly composed of a master robot arm that can be driven by a human operator, of a slave robot arm carrying out the task to be performed, and of an interface universe linking the master and the slave surroundings. This kind of system is used for the implementation of remote tasks or to carry out missions in a hostile universe. In teleoperated devices, the human operator plays a main role in the command loop for which he or she is at the same time the supervisor of the mission and the driver of the master set, able to intervene at any moment in case of a problem in the slave surrounding. So he must be in symbiosis with the system that allows him to stay in contact with the telerobot: for this purpose the operator has to use an interface between the device he supervises and himself ( Wawak, Jolly-Desodt and Jolly 1997).

This interface must present relevant information to the human operator at each moment. The problem in teleoperation systems is that data used to manage the device come from a great number of different sensors placed in various places of the teleoperation site, the complexity of such devices increasing continually.

The interface cannot present all this data to the operator at one time because he or she would be unable to cope with so much information.

Due to the lack of reliability of certain sensors at some times, the system has to filter the data before displaying on them interface. Data fusion techniques can manage both the aggregation and filtering functions.

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