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dc.contributor.author陈梅芬en_US
dc.contributor.author蔡文祥en_US
dc.date.accessioned2014-12-12T01:34:34Z-
dc.date.available2014-12-12T01:34:34Z-
dc.date.issued2008en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT079657515en_US
dc.identifier.urihttp://hdl.handle.net/11536/43523-
dc.description.abstract本研究提出了一套智慧型自动车系统,利用超音波讯号分析,让自动车能具有跟随使用者行走,并同时学习路径、与人互动、做路径分析,以及进行智慧型导航等功能。我们利用一台具有超音波感测器的自动车作为实验平台,使其航行于室内走廊环境中。针对跟随人物,我们提出了一个利用超音波和模糊控制来让自动车动态跟随使用者的方法。另外,为了能让使用者与自动车互动以下达控制指令,我们提出了一个分析使用者的行为以取得控制指令的方法,先以超音波侦测使用者的行走轨迹和特定姿势,再利用投票的方式来决定使用者对自动车所下达的控制指令。在学习完路径后,我们提出了一个自动分析路径的方法,能经由学习过的路径分析出导航时所需的转弯参数等资讯。接着,我们提出了一个利用超音波和模糊控制进行导航的方法,在导航时,利用墙壁资讯作为环境特征,并使用所设计的模糊控制器结合路径资讯和超音波讯号,来调整自动车的方向。我们还提出了一个能在导航时利用转弯参数和超音波以判断是否抵达转弯点的方法。最后我们以成功的学习和导航实验证明了本系统的完整性与可行性。zh_TW
dc.description.abstractAn intelligent autonomous vehicle system for learning and vehicle guidance in indoor environments is proposed. The system has several capabilities: learning paths by person following, interaction with humans, path analysis, and navigation as a guide. An autonomous vehicle equipped with ultrasonic sensors is used as a test bed. First, a method for person following in an environment is proposed, which has two fuzzy controllers for following a person dynamically. The fuzzy controllers adjust the vehicle’s direction and speed. Furthermore, to interact with humans, a technique for analyzing human behaviors is proposed, which analyzes a person’s walking trajectory by ultrasonic signals and uses a voting technique to obtain human commands implied by the walking postures. After learning, a method for path analysis is proposed, which analyzes the learned path data to estimate certain turning parameters for navigation. In addition, a method for vehicle navigation guidance by the use of the ultrasonic signal sequence and a fuzzy controller is proposed. The main environment feature used for navigation is wall. The fuzzy controller combines some information obtained from path analysis with ultrasonic signals to adjust the vehicle’s navigation direction. A technique for detecting learned turning points is also proposed, which decides whether the vehicle arrives at a turning point or not, using learned data and ultrasonic signals as well. Good experimental results show the flexibility and feasibility of the proposed system for the applications of person following, path analysis, and people guiding in indoor environments.en_US
dc.language.isoen_USen_US
dc.subject模糊控制zh_TW
dc.subject自动车zh_TW
dc.subject学习zh_TW
dc.subject导航zh_TW
dc.subject超音波zh_TW
dc.subject声纳zh_TW
dc.subject跟人zh_TW
dc.subject路径分析zh_TW
dc.subject模糊zh_TW
dc.subjectfuzzy logic control systemen_US
dc.subjectfuzzy controlleren_US
dc.subjectfuzzyen_US
dc.subjectfuzzy controlen_US
dc.subjectmobile roboten_US
dc.subjectautonomous vehicleen_US
dc.subjectlearningen_US
dc.subjectnavigationen_US
dc.subjectultrasonic sensoren_US
dc.subjectultrasonicen_US
dc.subjectsonaren_US
dc.subjectperson followingen_US
dc.subjecthuman followingen_US
dc.subjectpath analysisen_US
dc.subjectguidanceen_US
dc.title利用超音波讯号分析与模糊控制技术作室内自动车学习与导航之研究zh_TW
dc.titleA Study on Automatic Learning and Guidance for Indoor Autonomous Vehicle Navigation by Ultrasonic Signal Analysis and Fuzzy Control Techniquesen_US
dc.typeThesisen_US
dc.contributor.department多媒体工程研究所zh_TW
显示于类别:Thesis


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