Control techniques for collaborative and cooperative robotic systems

Overtheyears, theindustrial landscapehasexperiencedsignificantevolutionsdrivenby advancementsintechnology,economicfluctuations,shiftsinsocietalandenvironmental dynamics,andevolvingconsumerpreferences.Thesechangeshaveresultedinfundamental alterations inthewaybusinessesoperate, impactingvariousaspectsof the industry, includingtheadoptionoftechnology, laborpractices,businessmodels,andsustainability initiatives. Theever-changingindustrial environment ismarkedbyseveral emergingfrontiers thatembraceontheonehandtheincorporationofdigitaltechnologies,cyber-physical systems,artificial intelligence,andtheinternetofthingsintomanufacturingprocesses withthepotential for futuredevelopments, suchas Industry5.0,whichemphasizes theadvancementofcollaborativeroboticsystems. Industry5.0, inparticular,placesa significantemphasisonhuman-robotcollaboration(HRC)byvaluinghumaninput. Ontheotherhand, theleading-edgefrontiersinvolveincorporatingsensorsanddata analyticsintointelligentinfrastructure,whichservestoelevatemaintenancestandards, minimizedowntime,andenhancesafety.Thisalsoentailsleveragingcooperativerobotmachinesystems, suchasdronesanddiagnostictrains, for infrastructure inspections. Thesemeasurescontributetocostreductionandefficiencyenhancementinthemonitoring andmaintenanceprocesses. Intheindustrialsector,arealmofnewprospectsisemerging, drivenbytheinnovativedevelopmentof last-miledeliverysolutions,encompassingdrone deliveries,autonomousdeliveryvehicles,andsmart lockers,alldesignedtostreamline urbanlogistics. Asaresult, thisthesis isdedicatedtosolvingtwoof themost importantresearch challenges indesigningdecisionandcontrol techniquesforcollaborativeandcooperative roboticsystemsandinparticularforHRCandaerial-groundmobileroboticsystems. In thefirst part, this thesis aims toaddress the gaps identified in the existing literatureregardingsafe,ergonomic,andefficientHRC,whichhavebeenbroughttolight throughacomprehensivereviewconductedinthisfield. Inparticular, thedeveloped contributionsregardtheconceptualizationanddevelopmentofnovelarchitecturesand controltechniquesforHRC, inpresenceorabsenceofoptimization.Thecentralaimisto concurrentlyoptimizethethreekeyobjectives, i.e.,safety,ergonomics,andefficiencyin tasksassociatedwithaddressingthetrajectoryplanningproblemformulatedassecondorder coneprogrammingproblemand solvedwith thedirect transcriptionmethod, whilerespectingthespeedandseparationmonitoring(SSM)ISOsafetyrequirementand guaranteeingtheergonomicoptimalpositionof theoperatorduringthecollaborative phase.ExpandingupontheessentialcriteriaforasafeandergonomicHRCtoencompass theemergingdomainofcollaborationbetweenhumananddrone,thesecondgoal involves creatingcontrolalgorithms, i.e., linearquadraticregulator (LQR)controllers, forsystems involvinghumansanddroneswithinindoorindustrialsettingslikewarehouses4.0. Thesecondpartofthisthesis isfocusedonthecooperationbetweenafleetofdrones oranindividualdroneandagroundmobileroboticsystem(i.e., train, truck)thatentails theseentitiesworkinginharmonytoachievespecificobjectivesortasks inacoordinated manner.Particularemphasisisplacedonthecriticalphaseofdronesreturningtoand landingonamovingtrainor truck. Thus, ad-hoccontrol techniques, i.e., consensus algorithm, LQR and receding horizon LQR controllers, are presented to tackle such complext asks in an efficient and effective way.