博碩士論文 105327004 完整後設資料紀錄

DC 欄位 語言
DC.contributor光機電工程研究所zh_TW
DC.creator蘇許武zh_TW
DC.creatorHsu-Wu Suen_US
dc.date.accessioned2018-8-15T07:39:07Z
dc.date.available2018-8-15T07:39:07Z
dc.date.issued2018
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=105327004
dc.contributor.department光機電工程研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract本論文將使用Arduino作為主控,利用IMU融合四元數之算法偵測機身俯仰、翻滾、偏航之角度及角速度,並且透過多層PID的結構進行負回授控制以實現機身的自平衡,機器視覺方面是使用RaspberryPi作為影像處理之工具,並將解算後的訊號透過UART回傳至Arduino對姿態進行補償,其中有利用光流法實現懸停,以及霍夫轉換實現追蹤地面目標,本論文將會介紹系統架構、姿態算法、PID回授控制結構、感測器校正、以及如何使用機器視覺補償姿態之原理。zh_TW
dc.description.abstractThesis will use Arduino as the main control, using IMU fusion quaternion algorithm to detect the pitch, roll, yaw angle and angular velocity of the fuselage, and negative feedback control through the structure of multi-layer PID to achieve self-balancing of the fuselage, In machine vision, RaspberryPi is used as a tool for image processing, and the decoded signal is transmitted back to the Arduino through the UART to compensate for the attitude. Among them, the optical flow method is used to achieve hovering, and the Hough transform is used to track the ground target. thesis will introduce the system architecture, attitude algorithm, PID feedback control structure, sensor calibration, and how to use machine vision to compensate for the attitude.en_US
DC.subject四軸機zh_TW
DC.subject機器視覺zh_TW
DC.subject光流zh_TW
DC.subject霍夫轉換zh_TW
DC.subject四元數zh_TW
DC.subjectArduinoen_US
DC.subjectRaspberryPien_US
DC.subjectQudacopteren_US
DC.subjectMachine Visionen_US
DC.subjectOptical flowen_US
DC.subjectHough transformen_US
DC.subjectIMUen_US
DC.subjectquaternionen_US
DC.title四軸機結合機器視覺之開發zh_TW
dc.language.isozh-TWzh-TW
DC.titleQuadcopter combined with machine vision developmenten_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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