Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/154053
Title: Embedded system application development on Raspberry Pi 3 mock-up self-learning vehicle
Authors: Wang, Yuanchen
Keywords: Engineering::Electrical and electronic engineering::Applications of electronics
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Wang, Y. (2021). Embedded system application development on Raspberry Pi 3 mock-up self-learning vehicle. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154053
Project: P3016-201
Abstract: In recent years, many tech giants like Tesla, Amazon and Apple are developing autonomous vehicles eagerly to take the lead in the delivery and transportation industries in the near future. Experts and CEOs of tech giants predicted that we are just decades away from fully autonomous vehicles. Therefore, it is very challenging and rewarding to study and build a mock-up self-driving vehicle for this project. This project aims to design and build a mock-up autonomous vehicle with Raspberry Pi 3B plus as core module. Other hardware includes Pi camera, gearbox, motor, voltage regulator and L298N module are integrated to achieve autonomous control. Thonny IDE(Python) is being used as the developing tool since it is the default program of the Raspbian system. Python programming language is relatively user-friendly as it has English-like syntax and easier to read and understand. In this project, Thonny has been installed on PC for training data pre-processing and model training as Raspberry Pi has limited computing power and over-heating when heavily loaded.
URI: https://hdl.handle.net/10356/154053
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP_Report_Wang Yuanchen_U1620514B.pdf
  Restricted Access
3.99 MBAdobe PDFView/Open

Page view(s)

91
Updated on Nov 28, 2022

Download(s) 50

18
Updated on Nov 28, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.