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Factor analysis of the Polish version of Godspeed questionnaire (GQS)

100%

Szczepanowski R. , Niemiec T. , Cichoń E. , Arent K. , Florkowski M. , Sobecki J.

tom Vol. 16, No. 2

30--35

The rapid development of robotics involves human‐robot interaction (HRI). It is a necessary to assess user satis‐ faction to develop HRI effectively. Thus, HRI calls for in‐ terdisciplinary research, including psychological instru‐ ments such as survey questionnaire design. Here, we pre‐ sent a factor analysis of a Polish version of the Godspeed Questionnaire (GSQ) used to measure user satisfaction. The questionnaire was administered to 195 participants. Then, factor analysis of the GSQ was performed. Finally, reliability analysis of the Polish version of the GSQ was done. The adapted version of the survey was characte‐ rized by a four‐factor structure, i.e., anthropomorphism, perceived intelligence, likeability, and perceived safety, with good psychometric properties.

An NLP-based approach for improving human-robot interaction

86%

Kilicaslan Y. , Tuna G.

tom Vol. 3, No. 3

189--200

This study aims to explore the possibility of improving human-robot interaction (HRI) by exploiting natural language resources and using natural language processing (NLP) methods. The theoretical basis of the study rests on the claim that effective and efficient human robot interaction requires linguistic and ontological agreement. A further claim is that the required ontology is implicitly present in the lexical and grammatical structure of natural language. The paper offers some NLP techniques to uncover (fragments of) the ontology hidden in natural language and to generate semantic representations of natural language sentences using that ontology. The paper also presents the implementation details of an NLP module capable of parsing English and Turkish along with an overview of the architecture of a robotic interface that makes use of this module for expressing the spatial motions of objects observed by a robot.

Psychologiczne aspekty interakcji człowiek-robot

72%

Rudnicka P.

tom vol. 3

53--59

W ostatnich latach obserwować możemy intensywny rozwój robotyki i ekspansję robotów poza zastosowania w przemyśle, wojsku czy medycynie. Coraz większa dostępność cenowa sprawia, że obecność robotów w domach, pełniących różnorodne funkcje od sprzątania poprzez rozrywkę staje się czymś coraz bardziej powszechnym. Roboty to najbardziej zaawansowane technologicznie maszyny stworzone przez człowieka i przez niego używane. Projektowanie i konstruowanie robotów, pełniących nowe role współpracowników, towarzyszy i opiekunów, a przede wszystkim wprowadzanie ich do użytku na skalę masową, stawia nowe wyzwania przed wieloma dziedzinami nauki stanowiącymi podstawę nowej dyscypliny jaką jest interakcja człowiek-robot (HRI, Human-Robot Interaction). Celem tego artykuły jest przybliżenie psychologicznych zagadnień związanych z interakcją człowiek-robot w obszarze robotyki medycznej.

In recent years we observe the rapid development in the field of robotics and robots expansion beyond manufacturing, military, and medical domain. Becoming increasingly affordable makes robots’ presence in households, where they are performing a variety of functions from cleaning through entertainment, something more and more common. Robots are the most technologically advanced machines created by humans and destined to serve them. To design and construct a robot performing new roles of workplace peers, companions caretakers, and guardians and to turn them into a mass product presents challenges for Human- Robot Interaction (HRI). The purpose of this paper is to outline psychological issues related to HRI in the specific field of medical robotics.

HMM-based phoneme speech recognition system for the control and command of industrial robots

58%

Naik A.

tom Vol. 118, iss. 1

art. no. e2021002

n recent years, the integration of human-robot interaction with speech recognition has gained a lot of pace in the manufacturing industries. Conventional methods to control the robots include semi-autonomous, fully-autonomous, and wired methods. Operating through a teaching pendant or a joystick is easy to implement but is not effective when the robot is deployed to perform complex repetitive tasks. Speech and touch are natural ways of communicating for humans and speech recognition, being the best option, is a heavily researched technology. In this study, we aim at developing a stable and robust speech recognition system to allow humans to communicate with machines (robotic-arm) in a seamless manner. This paper investigates the potential of the linear predictive coding technique to develop a stable and robust HMM-based phoneme speech recognition system for applications in robotics. Our system is divided into three segments: a microphone array, a voice module, and a robotic arm with three degrees of freedom (DOF). To validate our approach, we performed experiments with simple and complex sentences for various robotic activities such as manipulating a cube and pick and place tasks. Moreover, we also analyzed the test results to rectify problems including accuracy and recognition score.