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Artificial Intelligence and Deep Learning Applications in Crop Harvesting Robots -A Survey

Tanmay U. Sane, Tanuj Sane

Year
2021
Citations
10

Abstract

With the ever-growing population, demand of good quality food has also increased. This demand is also constrained by shortage of skillful labor & involved costs. Considering these, efforts have been made to automate and improve current crop harvesting processes, using advancements in artificial intelligence (AI) and deep learning (DL) algorithms. This paper explores various robotic harvesting systems, which have already implemented or plan to utilize such techniques to detect a crop, navigate to it and efficiently harvest it in a reliable way. The paper states the harvested crop, investigates the selection criteria of an AI/ DL method, the respective benefits & challenges faced in its field implementation. Lastly, the paper states the possible metrics for selection of such a method and finds that Convoluted Neural Networks (CNN) are a popular choice of DL method for such applications based on their robustness and performance.

Keywords

Robustness (evolution)Artificial intelligenceComputer scienceEconomic shortageDeep learningMachine learningRobotField (mathematics)PopulationArtificial neural network

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