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The effect of data visualisation quality and task density on human-swarm interaction.

Abioye, A. O., Naiseh, M., Hunt, W., Clark, J., Ramchurn, S. D. and Soorati, M. D., 2023. The effect of data visualisation quality and task density on human-swarm interaction. In: 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 28-31 August 2023, Busan, South Korea, 1494-1501.

Full text available as:

IEEE_RO_MAN_2023_paper (002).pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.


Official URL:

DOI: 10.1109/RO-MAN57019.2023.10309454


Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this paper, we study the human factors aspect of the human-swarm interaction and investigate how having access to high-quality data can affect the performance of the human-swarm system - the number of tasks completed and the human trust level in operation. We designed an experiment where a human operator is tasked to operate a swarm to identify casualties in an area within a given time period. One group of operators had the option to request high-quality pictures while the other group had to base their decision on the available low-quality images. We performed a user study with 120 participants and recorded their success rate (directly logged via the simulation platform) as well as their workload and trust level (measured through a questionnaire after completing a human-swarm scenario). The findings from our study indicated that the group granted access to high-quality data exhibited an increased workload and placed greater trust in the swarm, thus confirming our initial hypothesis. However, we also found that the number of accurately identified casualties did not significantly vary between the two groups, suggesting that data quality had no impact on the successful completion of tasks

Item Type:Conference or Workshop Item (Paper)
Group:Faculty of Science & Technology
ID Code:39658
Deposited By: Symplectic RT2
Deposited On:03 Apr 2024 15:52
Last Modified:03 Apr 2024 15:52


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