Robot Cubes Construction System with Image Processing and Motor Control Functionality

碩士 === 國立臺灣海洋大學 === 電機工程學系 === 106 === With the development of science and technology, tailor-made robots have gained more functionality and variety. Towards the demand of each user, this thesis is aimed at developing a robot construction system. Using the system, the user can design and assemble ro...

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Bibliographic Details
Main Authors: Chang, Yao-Lin, 張曜麟
Other Authors: Cheng, Chih-Yung
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/r5xwxb
Description
Summary:碩士 === 國立臺灣海洋大學 === 電機工程學系 === 106 === With the development of science and technology, tailor-made robots have gained more functionality and variety. Towards the demand of each user, this thesis is aimed at developing a robot construction system. Using the system, the user can design and assemble robots by integrating different functionality modules. This concept can simplify the creation task and inspire user’s imagination to build a customized robot For simplicity, each module is designed as a cube and it can resist shaking and slippery. These blocks can be produced by 3D printing. The layout of the circuit boards inside is done by Protel99SE and can be produced as printed circuit boards. Inside the module, Arduino pro mini chip is used as the main controller. The controller can be equipped with other actuator or sensor devices which include OLED display, gyro, infrared sensor, DC gear motor, servomotor or camera. For the firmware design, abundant open-source codes of Arduino can be used and integrated. It helps user easily write the code to control the robot. Additionally, a camera module is designed in order to operate the robot remotely. Further, the camera module is equipped with image processing capability; therefore it can provide robot the target distance and direction information. Two mobile robots are first demonstrated to show the effectiveness of the system. One is the line-following robot and the other is the balanced robot. The line-following car uses the infrared sensor module to detect line and directs DC gear motor module to follow. The balanced robotic car uses the gyro sensor module and parameter/OLED module to adjust and display PID control gains. The user can tune the knob and experience the power of control theory directly. Another vision-based robot is demonstrated to test the intelligent camera module. The module uses Raspberry Pi Zero W board as the main processor. Python codes for image processing are developed to help robot determine the distance and direction of the target. The robot can then track and grasp the target autonomously. This system includes mechanism, circuits, software and control theory design. It hopes the user can develop his/her personal style robot easily. Also, the system can be of great help in control or robotics education.