Literature DB >> 28802443

Controlling robots in the home: Factors that affect the performance of novice robot operators.

Conor McGinn1, Aran Sena2, Kevin Kelly2.   

Abstract

For robots to successfully integrate into everyday life, it is important that they can be effectively controlled by laypeople. However, the task of manually controlling mobile robots can be challenging due to demanding cognitive and sensorimotor requirements. This research explores the effect that the built environment has on the manual control of domestic service robots. In this study, a virtual reality simulation of a domestic robot control scenario was developed. The performance of fifty novice users was evaluated, and their subjective experiences recorded through questionnaires. Through quantitative and qualitative analysis, it was found that untrained operators frequently perform poorly at navigation-based robot control tasks. The study found that passing through doorways accounted for the largest number of collisions, and was consistently identified as a very difficult operation to perform. These findings suggest that homes and other human-orientated settings present significant challenges to robot control.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Human-robot interaction; Man-machine interaction; User-centered design; Virtual reality

Mesh:

Year:  2017        PMID: 28802443     DOI: 10.1016/j.apergo.2017.05.005

Source DB:  PubMed          Journal:  Appl Ergon        ISSN: 0003-6870            Impact factor:   3.661


  3 in total

1.  Designing Gestures of Robots in Specific Fields for Different Perceived Personality Traits.

Authors:  Jin Niu; Chih-Fu Wu; Xiao Dou; Kai-Chieh Lin
Journal:  Front Psychol       Date:  2022-06-23

2.  Assessment of Perceived Attractiveness, Usability, and Societal Impact of a Multimodal Robotic Assistant for Aging Patients With Memory Impairments.

Authors:  Justyna Gerłowska; Urszula Skrobas; Katarzyna Grabowska-Aleksandrowicz; Agnieszka Korchut; Sebastian Szklener; Dorota Szczęśniak-Stańczyk; Dimitrios Tzovaras; Konrad Rejdak
Journal:  Front Neurol       Date:  2018-06-01       Impact factor: 4.003

3.  Improving Eye-Computer Interaction Interface Design: Ergonomic Investigations of the Optimum Target Size and Gaze-triggering Dwell Time.

Authors:  Ya-Feng Niu; Yue Gao; Ya-Ting Zhang; Cheng-Qi Xue; Li-Xin Yang
Journal:  J Eye Mov Res       Date:  2020-09-25       Impact factor: 0.957

  3 in total

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