與機(jī)器人有關(guān)的研究具有很深的歷史背景,對(duì)人類的生活有著重要的影響。機(jī)器人在工業(yè)、家庭服務(wù)、醫(yī)療上有眾多的應(yīng)用。從1985年以來,機(jī)器人在神經(jīng)外科、骨科手術(shù)和其他各種醫(yī)學(xué)學(xué)科中產(chǎn)生了深遠(yuǎn)的影響。使用不同的方法來改善病人護(hù)理的需求不斷增加,這對(duì)機(jī)器人的精度和準(zhǔn)確性提出了更高的要求。機(jī)器人跨越時(shí)間和領(lǐng)域的應(yīng)用可以說明趨勢(shì)是顯而易見的,這意味著未來的醫(yī)療機(jī)器人前景十分光明。從人機(jī)交互的角度出發(fā),自主機(jī)器人控制的許多應(yīng)用被開發(fā)出來。在這里,我們使用Delta機(jī)器人有三個(gè)驅(qū)動(dòng)元件來驅(qū)動(dòng)它的末端執(zhí)行器。在醫(yī)學(xué)領(lǐng)域,機(jī)器人需要更高的準(zhǔn)確度和精密度,所以這里我們使用兩個(gè)不同的接口來控制。一個(gè)是通過使用攝像機(jī)來實(shí)現(xiàn)實(shí)時(shí)眼動(dòng)跟蹤,另一個(gè)是通過鍵盤輸入末端執(zhí)行器的位置。這種手動(dòng)輸入選項(xiàng)將在相機(jī)發(fā)生故障自動(dòng)眼鏡追蹤功能失效的時(shí)候發(fā)揮作用。本文將Galil運(yùn)動(dòng)控制器應(yīng)用于眼科治療的臨床應(yīng)用中,對(duì)Delta機(jī)器人的發(fā)展進(jìn)行了論證。這項(xiàng)工作減少了醫(yī)生的工作量,節(jié)約了醫(yī)生的時(shí)間。使用該模型,醫(yī)生不需要涉及患者的身體,然而,該模型具有面部檢測(cè)和眼睛檢測(cè)的能力,不僅可以在眼睛專家的臨床應(yīng)用中實(shí)現(xiàn),而且可以實(shí)時(shí)實(shí)時(shí)地跟蹤患者... 

【文章來源】：哈爾濱工業(yè)大學(xué)黑龍江省 211工程院校 985工程院校

【文章頁數(shù)】：68 頁

【學(xué)位級(jí)別】：碩士

【文章目錄】：
摘要
Abstract
Chapter 1 Introduction
    1.1 Source of Project
    1.2 Project Background and Significance
    1.3 Literature Review
        1.3.1 Historical Background
        1.3.2 Computer vision & Image Processing in Robotics
        1.3.3 Delta robot in medical field
        1.3.4 Robotics in Cardiovascular
        1.3.5 Robotic in Ophthalmic Surgery
    1.4 Problem Statement
    1.5 Aims and Objectives
    1.6 Thesis Outline
    1.7 Brief Summary of Chapter
Chapter 2 Structure Design and Kinametic Analysis
    2.1 Introduction
    2.2 Basic Structure of Model
    2.3 The Designing of the delta parallel structure
    2.4 Architectural Determination of Structure
    2.5 Kinematic Analysis
        2.5.1 Forward Kinematics
        2.5.2 Inverse Kinematics
    2.6 Verification of Kinematics Solutions
    2.7 Brief Summary of Chapter
Chapter 3 Image Processing
    3.1 Introduction
    3.2 Theoretical Background
    3.3 Object Detection
    3.4 Sample Detection by Color
    3.5 Introduction of Haar-like Features
    3.6 Cascade Classifier
    3.7 Related Work
        3.7.1 Pure Tech System of Car Counting
        3.7.2 Autonomous Real-time vehicle detection from a medium-level UAV
        3.7.3 Monocular Vehicle detection and tracking
    3.8 Object Detection using Haar-Cascade classifier
    3.9 Brief Summary of Chapter
Chapter 4 Methodology & Experimental Results
    4.1 Introduction
    4.2 Controller
        4.2.1 Galil Motion Controller
        4.2.2 Actuators
        4.2.3 Amplifier
        4.2.4 Encoder
        4.2.5 Timer
        4.2.6 Software
    4.3 Control Technique
    4.4 Programming
    4.5 Camera
    4.6 Experiment and Results
        4.6.1 Position tracking of Delta Robot
        4.6.2 Eye Tracking
        4.6.3 Experimental validation
        4.6.4 Dual operating Characteristics
    4.7 Brief Summary of Chapter
Conclusion
References
Acknowledgement



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