Autonomous Farming: Modeling andControl ofAgricultural Machinery ina Unified Framework

Currently, there aresignificant challenges facedmachinery, ifthefarmland layout andthecropplantation can bythefarming industry, notleast ofwhichareareduction bestructured. Primarily theaimistoachieve adesirable crop intheavailable labour workforce, anda more'corporate' plantation pattern withrespect toaglobal coordinate frame. style offarming. Suchfactors demandanincrease infarmingDetermining thecropplantation patter isnotatrivial task. It efficiency andproductivity. Thispaperlooks forward tothe D es the cropitstiontour ma the task.tIc nottoodistant future, wheretherealisation ofautonomous involves thelandgeometry, itscontour map,thegeometric farming will aidinthefarming communities surviving aswell as parameters oftheavailable machinery andthecropbeing competing intheglobal market. Inthis work, theautonomous planted. Inaddition, anumberofagronomical constraints farmisseenasacomplex system-of-systems, wherethere is will playarole. Nevertheless, this task canbecarried outoff- necessarily a seamless integration ofrequirements, bringingline before cropplantation isstarted. Itisobvious that, toen- together theareas ofrobotics forautonomous farming, and surebefore croplayout, seed. It becat,t Precision Agriculture (PA), whichdeals withissues ofagron-sureastructured croplayout, seeding mustbecarried outas omy.Inessence, agricultural robotics uses on-farm sensing and specified toensure precision cropplantation. Thecomplexity control toactuate autonomous farmmachinery withtheaim oftheoperation andthesub-inch precision required, rules ofsatisfying agronomy-based objectives. We initially describeoutthehumanoperators. Especially inbroad acrefarming, asystem-of-systems architecture, orunified framework, where avital building block istheexistence oftwodatasets used operating massive machaiery generally rated around 200to aslinks, orcommunication, between thevarious sub-systems. 400horsepower, tomaintain sub-inch seeding accuracy over Thesedatasets include aPrecision Farming DataSet(PFDS)often vast distances isimpractical. Suchaccuracy essentially formed off-line before cropcultivation, containing spatially pre-requires autonomous agricultural vehicles. cise navigation dataforanyandall autonomous machinery, and Attheresearch level, there areanumberoffronts pro- aPrecision Agriculture DataSet(PADS), whichisacontinually .

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