A fuzzy data-based model for Human-Robot Proxemics
Paper in 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

Author

Tomasz Kosinski

Chalmers, Applied Information Technology (Chalmers), Interaction design

Mohammad Obaid

Chalmers, Applied Information Technology (Chalmers), Interaction design

Pawel Wozniak

Chalmers, Applied Information Technology (Chalmers), Interaction design

Morten Fjeld

Chalmers, Applied Information Technology (Chalmers), Interaction design

J. Kucharski

Lodz University of Technology

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

1944-9437 (eISSN)

335-340
978-1-5090-3929-6 (ISBN)

Areas of Advance

Information and Communication Technology

Subject Categories

Computer Systems

DOI

10.1109/ROMAN.2016.7745152

ISBN

978-1-5090-3929-6

More information

Latest update

9/6/2018 2