Multi-agent Task Allocation for Fruit Picker Team Formation (Extended Abstract)

Harman, Helen and Sklar, Elizabeth (2022) Multi-agent Task Allocation for Fruit Picker Team Formation (Extended Abstract). In: The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022).

Full content URL: https://dlnext.acm.org/doi/proceedings/10.5555/353...

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Multi-agent Task Allocation for Fruit Picker Team Formation (Extended Abstract)
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Abstract

Multi-agent task allocation methods seek to distribute a set of tasks fairly amongst a set of agents. In real-world settings, such as fruit farms, human labourers undertake harvesting tasks, organised each day by farm manager(s) who assign workers to the fields that are ready to be harvested. The work presented here considers three challenges identified in the adaptation of a multi-agent task allocation methodology applied to the problem of distributing workers to fields. First, the methodology must be fast to compute so that it can be applied on a daily basis. Second, the incremental acquisition of harvesting data used to make decisions about worker-task assignments means that a data-backed approach must be derived from incomplete information as the growing season unfolds. Third, the allocation must take “fairness” into account and consider worker motivation. Solutions to these challenges are demonstrated, showing statistically significant results based on the operations at a soft fruit farm during their 2020 and 2021 harvesting seasons.

Keywords:multi-agent system, multi-robot system, task allocation, fruit harvesting
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
Divisions:College of Science > Lincoln Institute for Agri-Food Technology
ID Code:49037
Deposited On:26 Jul 2022 14:31

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