A fuzzy data-based model for Human-Robot Proxemics
Paper i proceeding, 2016

This work aims at bringing empirical knowledge on Human-Robot Interaction obtained from user studies closer to being integrated into the capabilities of robots currently available on the market. The Takagi-Sugeno-Kang method and results of a user study conducted with thirty two participants were used to build a fuzzy data-based model for Human-Robot Proxemics. The experiment investigated the effect of robot approach distance and angle on perceived human comfort. The proposed model, consisting of a set of rules, fuzzy sets and their parameters, can be used by the robotics community thanks to their formal form. It can also be directly translated into natural language statements. Results of model cross-validation are reported.

human-robot proxemics

fuzzy data-based model

fuzzy logic

Human-Robot Interaction

Författare

Tomasz Kosinski

Chalmers, Tillämpad informationsteknologi, Interaktionsdesign (Chalmers)

Mohammad Obaid

Chalmers, Tillämpad informationsteknologi, Interaktionsdesign (Chalmers)

Pawel Wozniak

Chalmers, Tillämpad informationsteknologi, Interaktionsdesign (Chalmers)

Morten Fjeld

Chalmers, Tillämpad informationsteknologi, Interaktionsdesign (Chalmers)

J. Kucharski

Politechnika Lodzka

Robot and Human Interactive Communication (RO-MAN), 2016 25th IEEE International Symposium on

1944-9437 (eISSN)

335-340

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Datorsystem

DOI

10.1109/ROMAN.2016.7745152

ISBN

978-1-5090-3929-6

Mer information

Senast uppdaterat

2018-09-06