Transferring artificial intelligence practices between collaborative robotics and autonomous driving
ISSN: 0368-492X
Article publication date: 30 August 2022
Issue publication date: 25 September 2023
Abstract
Purpose
Collaborative robotics and autonomous driving are fairly new disciplines, still with a long way to go to achieve goals, set by the research community, manufacturers and users. For technologies like collaborative robotics and autonomous driving, which focus on closing the gap between humans and machines, the physical, psychological and emotional needs of human individuals becoming increasingly important in order to ensure effective and safe human–machine interaction. The authors' goal was to conceptualize ways to combine experience from both fields and transfer artificial intelligence knowledge from one to another. By identifying transferable meta-knowledge, the authors will increase quality of artificial intelligence applications and raise safety and contextual awareness for users and environment in both fields.
Design/methodology/approach
First, the authors presented autonomous driving and collaborative robotics and autonomous driving and collaborative robotics' connection to artificial intelligence. The authors continued with advantages and challenges of both fields and identified potential topics for transferrable practices. Topics were divided into three time slots according to expected research timeline.
Findings
The identified research opportunities seem manageable in the presented timeline. The authors' expectation was that autonomous driving and collaborative robotics will start moving closer in the following years and even merging in some areas like driverless and humanless transport and logistics.
Originality/value
The authors' findings confirm the latest trends in autonomous driving and collaborative robotics and expand them into new research and collaboration opportunities for the next few years. The authors' research proposal focuses on those that should have the most positive impact to safety, complement, optimize and evolve human capabilities and increase productivity in line with social expectations. Transferring meta-knowledge between fields will increase progress and, in some cases, cut some shortcuts in achieving the aforementioned goals.
Keywords
Acknowledgements
This paper forms part of a special section “CyberSystemic implications on the future of societies”, guest edited by Igor Perko.
Disclosure statement: The authors report no potential conflict of interest.
Citation
Zorman, M., Žlahtič, B., Stradovnik, S. and Hace, A. (2023), "Transferring artificial intelligence practices between collaborative robotics and autonomous driving", Kybernetes, Vol. 52 No. 9, pp. 2924-2942. https://doi.org/10.1108/K-05-2022-0679
Publisher
:Emerald Publishing Limited
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