Analyzing previous human-robot interaction implementation in agriculture: What can we learn from the past?

Elias, Alex, Galvez Trigo, Maria ORCID: https://orcid.org/0000-0001-6492-0955 and Camacho-Villa, Carolina 2025. Analyzing previous human-robot interaction implementation in agriculture: What can we learn from the past? Presented at: 2025 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2025), Melbourne, Australia, 4-6 March 2025. Item availability restricted.

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Abstract

With the recent shift from conventional industrial robots to more collaborative Human-Robot Interaction (HRI) robots1 within industries such as the agriculture sector, it has become essential to understand the challenges associated with the adoption of these robots to ensure a smooth integration with minimal resistance. As with all new technologies, there is often push-back when changing approaches and initiating new pathways within company operations, which can cause hesitation and even halt the adoption process. This paper draws from interviews with agricultural companies that have previ- ously attempted to implement robots requiring direct human interaction, focusing on individuals within those companies who had decision-making capabilities during the implementation process. From these interviews, a set of action principles has been developed based on transferable knowledge found within the participating companies. The main results of this user study highlight that previous implementation attempts, whether positive or negative, influence future adoption. The study also identifies the multitude of barriers surrounding the agricultural sector’s adoption of these technologies and suggests potential actions for companies to take to minimize the issues associated with implementing HRI robots. By identifying common successes and failures and contextualizing them for other companies to follow, this study aims to utilize lessons learned from past implementation attempts to shorten the learning curve and reduce hesitation in adopting HRI robots within the agricultural sector.

Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Computer Science & Informatics
Subjects:	Q Science > Q Science (General) S Agriculture > S Agriculture (General) T Technology > T Technology (General)
Date of First Compliant Deposit:	31 January 2025
Date of Acceptance:	3 December 2024
Last Modified:	31 Jan 2025 15:15
URI:	https://orca.cardiff.ac.uk/id/eprint/175732

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