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《机器人手爪数据采集、融合和传输系统的研制》由会员上传分享，免费在线阅读，更多相关内容在行业资料-天天文库。
1、机器人手爪数据采集、融合和传输系统的研制摘要几了确保机器人操作的、全，有必要测量机器人的腕力。然些机器森薪罢豁馨井蕊霓瓮煞:覆露擎菜望霜掣霍霆薰蒸赞案箭髻嚣文提出了一为了得出腕力和指力关系，进行了标定实验。实验数据被用来训练径向基函数(RBF)神经网络，得出的神经网络结构和参数用于数据融合。数据Foil.合的结果与实际的标定值相符合，说明本文所提估计方法的有效性。机器人为了灵巧地抓取物体，在手爪上配w了多种传感器，例如指力传感器、触觉传感器和距离传感器。我们研制了一套荃子DSP的系统，以实现传感器数据的采集、融合和传
2、输。该系统硬件w数据采集模块、DSP模块和CAN传输模块组成。该系统软件包括监控程序、初始化模块、看门狗模块、数据融合模块、CAN通信模块、数字量采集模块、正交编码脉冲计数模块和A/D中断服务程序。该系统实时地采集和融合手爪各传感器的信息，得到手爪与工件的安全连接状态，通过CAN总线传输给主控计算机。关键词:机器人手]咔传感器;数据融合，Sd.iT}.'}7G毖DSPCAN总线3DevelopmentofDataAcquisition,FusionandTransmissionSystemforRobotGrippe
3、rsABSTRACTInordertoensurethesafetyofoperationofrobots,itisnecessarytodetectthewristforceofrobots.Somerobots,however,e.g.,anextravehicularmobilerobot(EMR)cannotinstallawristforcesensorbecauseofthelimitationofitscondition.Anovelkindoftechniquetoestimatethewristfo
4、rcewithoutadditionalsensorsispresentedinthispaper,whichusesadatafusionmethodaccordingtotheoutputvariationsoffingerforcesensorsinagripper.Thecalibrationexperimentsareconductedtodetecttherelationshipbetweenthewristforceandfingerforces.Theexperimentaldataareusedto
5、trainaradialbasisfunction(RBF)artificialneuralnetwork,andtheconstructionandparametersofthenetworkareobtainedfordatafusion.Theresultsofdatafusionofthewristforceareconsistentwiththepracticalcalibrationvalues,whichprovestheeffectivenessofthewristforceestimatingtec
6、hniqueproposedinthispaper.Inordertograspdexterouslyobjectswiththegripper,robotsinstallsensorsintheirgrippers,suchasfingerforcesensors,tactilesensorsandadisplacementsensor.ADSPbasedsystemisdevelopedtoimplementdataacquisition,fusionandtransmissionofsensors.Thehar
7、dwareofthissystemconsistsofadataacquisitionmodule,aDSPmoduleandCANtransmissionmodule.Thesoftwareincludesamonitorprogram,aninitializationmodule,awatchdogmodule,adatafusionmodule,aCANtransmissionmodule,aquadratureencoderpulsecountmoduleandanA/Dinterruptservicepro
8、gram.Thesystemcollectsandfusesdataofsensorsinrealtime,obtainsthestatusofgraspingobjectswiththegripper,andsendsthisinformationtoahostPCthroughCANbusKeyWords:robotgripper,sens
