The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Multimodal Feedback in Human-Robot Interaction: An HCI-Informed Comparison of Feedback Modalities
|
|
Author(s): Maria Vanessa aus der Wieschen (University of Southern Denmark, Denmark), Kerstin Fischer (University of Southern Denmark, Denmark), Kamil Kukliński (Białystok University of Technology, Poland), Lars Christian Jensen (University of Southern Denmark, Denmark)and Thiusius Rajeeth Savarimuthu (University of Southern Denmark, Denmark)
Copyright: 2020
Pages: 28
Source title:
Robotic Systems: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-1754-3.ch049
Purchase
|
Abstract
A major area of interest within the fields of human-computer interaction (HCI) and human-robot interaction (HRI) is user feedback. Previous work in HCI has investigated the effects of error feedback on task efficiency and error rates, yet, these studies have been mostly restricted to comparisons of inherently different feedback modalities, for example auditory and visual, and as such fail to acknowledge the many possible variations within each of these modalities, some of which being more effective than others. This chapter applies a user-centered approach to investigating feedback modalities for robot teleoperation by naïve users. It identifies the reasons why novice users need feedback when demonstrating novel behaviors to a teleoperated industrial robot and evaluates both various feedback modalities designed to prevent errors and, drawing on document design theory, studies different kinds of visual presentation regarding their effectiveness in the creation of legible error feedback screens.
Related Content
|
Rashmi Rani Samantaray, Zahira Tabassum, Abdul Azeez.
© 2024.
32 pages.
|
|
Sanjana Prasad, Deepashree Rajendra Prasad.
© 2024.
25 pages.
|
|
Deepak Varadam, Sahana P. Shankar, Aryan Bharadwaj, Tanvi Saxena, Sarthak Agrawal, Shraddha Dayananda.
© 2024.
24 pages.
|
|
Tarun Kumar Vashishth, Vikas Sharma, Kewal Krishan Sharma, Bhupendra Kumar, Sachin Chaudhary, Rajneesh Panwar.
© 2024.
29 pages.
|
|
Mrutyunjaya S. Hiremath, Rajashekhar C. Biradar.
© 2024.
30 pages.
|
|
C. L. Chayalakshmi, Mahabaleshwar S. Kakkasageri, Rajani S. Pujar, Nayana Hegde.
© 2024.
30 pages.
|
|
Amit Kumar Tyagi.
© 2024.
29 pages.
|
|
|