{"title":"Artificial Intelligence and Deep Learning Applications in Crop Harvesting Robots -A Survey","authors":"T. U. Sane, Tanuj Sane","doi":"10.1109/ICECCE52056.2021.9514232","DOIUrl":null,"url":null,"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.","PeriodicalId":302947,"journal":{"name":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECCE52056.2021.9514232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.