Abstract

Cooperative small harvesting robots, mimicking a group of human pickers, have the potential to significantly reduce labor dependence in strawberry production. A tri-layered algorithm is investigated to effectively assign rows to robots with each robot incentivized to maximize its total number of picked strawberries within the fleet’s harvesting time. The proposed algorithm consists of a decentralized local auction and negotiation strategy as the primary phase with a centralized fallback algorithm that guarantees an assignment. The salient features of the algorithm are reduced communication time, scalability, constant time complexity in the decentralized phase, and ease of implementation. The proposed algorithm is evaluated in a Monte Carlo simulation and the superior performance (e.g., significantly reduced computational time) is observed when compared with a centralized approach. It is expected that this row negotiation algorithm can address an important gap in strawberry harvesting via cooperative, small harvesting robots.

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