Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88641
Title: Workload, awareness and automation in multiple-robot supervision
Authors: Wong, Choon Yue
Seet, Gerald
Keywords: DRNTU::Engineering::Mechanical engineering
Multiple Robots
Workload
Issue Date: 2017
Source: Wong, C. Y., & Seet, G. (2017). Workload, awareness and automation in multiple-robot supervision. International Journal of Advanced Robotic Systems, 14(3), 1-16. doi:10.1177/1729881417710463
Series/Report no.: International Journal of Advanced Robotic Systems
Abstract: Using a single human to supervise multiple robots helps to address manpower constraints while deriving the benefits of multiple-robot deployment such as efficiency and improved system reliability. However, it can also induce high supervisor workload and diminish situation awareness. This article explains workload and situation awareness. It reviews various studies related to human–robot systems to illustrate the effects and causes of workload and diminished situation awareness in such systems. The article reviews and discusses the application of automation to address workload and situation-awareness concerns. It also presents the issues that the use of automation can cause, highlighting that automation must be applied with care. The article advocates the consideration of sliding autonomy for four aspects of task execution: information acquisition, information analysis, decision selection and action implementation. It additionally encourages the appreciation for recognized methods of applying and triggering automation. The hope is for robots to be equipped with adjustable autonomy across multiple aspects of task performance to create robotic systems with highly flexible autonomy configurations. While robots from such systems may have the flexibility to deal with numerous situation requirements, the research challenge is understanding if and how such flexibility will affect human workload.
URI: https://hdl.handle.net/10356/88641
http://hdl.handle.net/10220/45867
ISSN: 1729-8806
DOI: http://dx.doi.org/10.1177/1729881417710463
Rights: © 2017 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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