LEARNING BASIC HUMAN GUIDING STYLES FOR MOBILE ROBOT

I. Nagy, P. Baranyi, P. Greguss

Abstract

The real-time control of mobile robots in uncertain, dynamic environments is one of the major fields of the current research. The main objective of this paper is to find a suitable method to model different styles of guiding. Motivated by the chosen algorithm’s (potential based guiding) limitations an extended method is presented. A common type neuro-fuzzy algorithm is developed which can approximate the proposed model. The extended model improves the modeling properties and eliminates some disadvantages of the PBG model.

Keywords

guiding model, PAL optic, autonom robots, neuro-fuzzy systems

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IMEKO-WC-2000-TC17-P452.pdf

DOI

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IMEKO TC

TC17 - Measurement in Robotics

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