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Page 1: Collaborative Teams of Heterogeneous Robots for ... · PDF fileCollaborative Teams of Heterogeneous Robots for Agricultural Applications ... – AFOSR DDDAS, Frederica Darema – NSF

CollaborativeTeamsofHeterogeneousRobotsforAgriculturalApplications

Asst.Prof.GirishChowdharyDirectorofDistributedAutonomousSystemslab

AgriculturalandBiologicalEngineering,CoordinatedSciencesLab,

InstituteforGenomicBiology,AerospaceEngineering,BeckmanInstitute

www.daslab.illinois.edu

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• Robotics– Smallagriculturalrobots– UnmannedAerialSystems

• Collaborative– Robotics– LearningfromHumandemonstrations

• FieldIntelligence:– Machinelearning– NeuralNetworks

• AdaptiveAutonomy– Adaptivecontrol– ReinforcementLearning

AdvancingtheScienceofAutonomy

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Group:1ResearchFaculty,1Postdocs,2ResearchEngineers,6PhDstudents,3MS,4researchassistants

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HighThroughputPhenotyping

• Phenotyping:Relatinggeneticstoplanttraits• Criticaltoefficientandproductivebreeding• Currentlylaborintensive

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DOEARPA-ETERRA-MEPP

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HerbicideResistantWeeds!

• Examples:5-waymultipleresistantWaterhemp andPalmerAmaranth• Currentcost5-6Billion,andontherise!• Mechanicalcontrolistheonlyevolutionarilysustainableway

ConfirmedGlyphosateresistantweedsinUS

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Wherearetheagrobots?

Mainchallenges:- Autonomy- Cost- Easeofuse

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CompactLow-CostUASarePractical

• Widelyadoptedconsumersystemsarelow-cost,simple,andmulti-purpose

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Aplug-and-playautopilotdesignedtoworkacrossseveralaerospacevehicles.

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OverviewofInversionBasedMRAC

�̇�𝑥 = 𝑓𝑓& 𝑥𝑥, 𝑢𝑢 + 𝑓𝑓 𝑥𝑥, 𝑢𝑢 − 𝑓𝑓& 𝑥𝑥, 𝑢𝑢

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ModelingerrorΔ ∈ ℜ.

n Combinedpseudo-controlaction:𝜈𝜈 = −𝐾𝐾𝐾𝐾 + �̇�𝑥23 − 𝜈𝜈45

n Trackingerrordynamics�̇�𝐾 = 𝐴𝐴𝐾𝐾 + 𝐵𝐵(𝜈𝜈45 − Δ)

rmx

Reference Model 1ˆ -f f

Adaptation Law

PD compensator

𝑢𝑢

pdn

adn-Adaptive Element

𝐾𝐾x𝑢𝑢crmn-cx +

n Approximateinversionmodel𝑓𝑓&

n Designapseudocontrol𝜈𝜈tominimizethetrackingerror:𝐾𝐾 = 𝑥𝑥 − 𝑥𝑥23

n

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AdaptiveSystems

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Plug-and-AdaptAutonomy

• ChowdharyG.,WuT.,CutlerM.,HowJ.P.,“RapidTransferofControllersBetweenUAVsusingLearningBasedAdaptiveControl”,IEEEInternationalConferenceonRoboticsandAutomation,2013.

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GP-MRAC:DisturbanceAdaptation

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§ Grande,Chowdhary,HowJAIS2014(ExperimentalValidationofBayesianNonparametricAdaptiveControlusingGaussianProcesses)

§ GP-MRAClearnshowthedisturbanceaffectforcesontheUAV

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CollaborativeRoboticTeams

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HumanCollaborativeRobots

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SmartRoboticTeamsforAgriculture

IntegrativeResearchGoals:• Autonomy• Multi-robotcollaboration• Cost• SeamlessHuman-Machineinteraction 15

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autonomousPathFollowingandobstacleavoidance

8xspeed

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Sensors

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AutonomousTestinginSorghumplots2017

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LanekeepingwithConvolutionalDNN

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CornCounting

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BroadLeafWeedDetection

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DevianceDetectionfromAerialImages

Fromtake-offtoactionability,in20minutesorless!23

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UIUCTeam• Deeproboticsandcrop-scienceexpertise• SuccessfulprototypesandmodularCyber-Physicalsystems• 16top5rankedengineeringprograms• Highlyaccomplishedfaculty:USDA– ARSchairstoFellowof

theRoyalSociety

SteveLong,CropScience AdamDavis,CropScienceUSDA-ARS

CarlBernacchi,CropScienceUSDA-ARS

SethHutchison,ECERoboticist

InstituteofGenomicBiology

GirishChowdhary,ABERoboticist

CoordinatedScienceLab 24

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Teamwork!• Team:

– Postdoctoralassociates:Erkan Kayacan– PostdoctoralFellow/ResearchAssistantProf:Chinmay Soman– PHD:AllanAxelrod,GirishJoshi,Harshal Maske,Anay Patnaik,DennisOsipychev,JoshuaWhitman– MS:Anwesa Chaudhari,BeauBarber,HunterYoung– ResearchEngineers:NolanReplogle,SriVuppala– ResearchAssistants:BenThompson,VolgaKarkaus,Zang Zhongzhong– Visitingfellow:AkihiroHiguti (UniversityofSao-PauloBrazil)

• Collaborators:– Sertack Karaman,AFOSRDDDPSA– Prabhakar Pagilla,ChristopherCrick,andCharlesAbramson,NSFNRI– SteveLong,CarlBernacchi DOE-ARPA-E– AdamDavis,Weedingswarmbots

• Support– ARPA-E– AFOSRYoungInvestigatorAward,JamesLawton– AFOSRDDDAS,FredericaDarema– NSFNRI– DOE– NASA

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EARTHSENSEAgricultural Intelligence

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Wheretofromhere?

• Agrobotsareheretostay• Challenges– Cost– Autonomy– Reliability– EaseofUse

• Whatwoulddriveadoption?

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Backup

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