基于cmac神经网络的智能助行机器人在线学习控制new

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1、万方数据2013年3月920卷第2期控制工程ControlEngineeringofChinaMar．20l3V01．20．No．2文章编号：1671-7848(2013)02-0295-06OnlineLearningControlOfanIntelligentMobilityAidUsingCMACNeuralNetworkFENGDong，ZHOUWu—xiao，XULi(CoUegeofElectricalEngineering，ZhejiangUniversity，Hangzhou310027

2、，P．R．China)Abstract：Amotorizedintelligentmobilityaid，namedZJUWalker，isdevelopedtohelptheelderlywalkeasily，safelyandindependentlyintheoutdoorenvironment．Anonlinelearningcontrolapproachtoimprovetheinterpretationofauser’Swalkingintentisproposed．Thisisimplem

3、entedbylearningauser’SoperatinghabitsintheassociativememoryofCMACneuralnetworks．ExperimentalresultsshowthattheCMAC—basedlearningcontrollercangreatlyincreasetheeaseandcomfortoftheinteractionbe—tween刁UWalkerandtheuser．Keywords：ZJUWalker；intelligent；CMAC；co

4、ntrolCLCnumber：TP27‘Documentcode：A基于CMAC神经网络的智能助行机器人在线学习控制冯东，周武啸，许力(浙江大学电气学院，浙江杭州310027)摘要：为了使老年人能够独立、安全、舒适地行走于户外环境，针对自行开发的智能助行机器人ZJUWalker，提出一种基于CMAC神经网络的在线学习控制算法。。CMAC神经网络模拟人的小脑结构，具有学习速度快、结构简单等特点。采用CMAC神经网络对用户的行走习惯进行关联记忆和在线学习，并理解用户的行走意图。实验结果验证了所提方法的有效性

5、，使助行机器人更加易于使用，提高了用户在使用过程中的舒适度。关键词：助行机器人；智能；CMAC；控制1IntroductionRoboticwalkingsupportsystemwillplayanim—portantroletoimprovethequalityoflifefortheelderlyintheagingsociety．nepotentialmarketformobilityaidswillbevastconsideringthecontinuousgrowingelderlypopu

6、lation．Conventionalcanesandwalkers，whicharetiringandnotsafeenoughfortheelderly，cannotfullysatisfythe．demandofsafetyandcomfortanymore．Introducingrobotictechnologyintoacon—ventionalwalkingsupportingsystemwillbeofgreatin-terest．Currentlywearedevelopingamoto

7、rizedintelligentmobilityaid，namedzJUWalker，tohelptheelderlyintheoutdoorenvironment．NotonlyCanitprovidewalk—ingstabilityandweightsupportasconventionalwalk—ers，butalsocallitleamauser’Soperatinghabitstounderstandthewalkingintent，es．timateauser’sgait—basedon

8、accelerometerdata，avoidobstaclesandpro‘videguidancethroughGPSmodule．Theobjectiveofthisworkistohelptheelderlywalkeasily，safelyandindependently，toaugmentauser’Swalkingabilitybutnotreplaceit．However，inthispaperwerestrictourat