智慧生產研究模組
Special Topics and Labs on Intelligent Manufacture
| 節 | 週四 |
|---|---|
2 09:00–09:50 | 智慧生產研究模組 CM218 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 | |
5 13:20–14:10 | 智慧生產研究模組 CM218 2 節連堂 |
6 14:20–15:10 |
* 根據陽明交大上課時間表所列
Unit 1_ROS程式設計基礎(陳建志): 機器人作業系統(Robot Operating System, ROS)是專為開發機器人所設計的開源軟體架構,如今ROS已風行全世界並支援各大廠牌的機器人(Universal Robots, ABB Manipulators, Faunc等)。ROS提供了硬體抽象、設備驅動、函式庫、可視化工具、軟體間訊息傳遞和軟體包管理等功能。ROS背後廣大的社群累積了龐大的能量,除了提供基本工具外,也包含各式各樣的演算法,使得開發者可猶如組裝積木般,一塊塊的將自己想要的機器人快速拼接起來,並專注於開發自己的應用。本課程將引導學生學會相關的ROS基礎與知識,並學會以ROS開發相關應用程式及引用open source資源。 Unit 2_Mathmetics for Machine Learning(馬清文): This course is design to provides on some essential mathematical foundations on which machine learning and artificial intelligence are based. Topics include 1) algebra foundations such as equations, functions, and graphs; 2) differential calculus such as derivatives and optimization; 3) linear algebra such as vector-matrix multiplication and matrix decomposition and; 4) statistics, probability and basic information theory. We will also write python codes to explore the concepts and technologies that are introduced in this course. Unit 3_Math and Deep Learning(魏澤人):Introducing math related topics to deep learning and AI. Unit 4_衛星影像處理(許志仲):介紹多光譜與高光譜影像特質、高光譜影像分析技術、以及發展趨勢。 Unit 5_腦機介面(許巍嚴) :介紹腦機介面概念、技術與應用
Unit 1_ROS程式設計基礎(陳建志):程式設計、資料結構、嵌入式系統或物聯網程式設計 Unit 2_Mathmetics for Machine Learning(馬清文): 1. Computer programming skill, especially Python and C. 2. College linear algebra, calculus and probability concepts. Unit 3_Math and Deep Learning(魏澤人):Python Unit 4_衛星影像處理(許志仲):Python, linear algebra, statics Unit 5_腦機介面(許巍嚴) :作業上可能會使用C語言、Matlab
Unit 1_ROS程式設計基礎(陳建志):課堂講授、投影片 Unit 2_Mathmetics for Machine Learning(馬清文):課堂講授、投影片 Web resource: Essential math for machine learning: https://www.edx.org/course/essential-math-for-machine-learning-python-editi-2 Unit 3_Math and Deep Learning(魏澤人): Unit 4_衛星影像處理(許志仲):課堂講授、投影片 Unit 5_腦機介面(許巍嚴) :課堂講授、投影片
Unit 1_ROS程式設計基礎(陳建志):作業成績 100% Unit 2_Mathmetics for Machine Learning(馬清文):Homework: 100% Unit 3_Math and Deep Learning(魏澤人):作業成績50%、出席50% Unit 4_衛星影像處理(許志仲):作業成績 100% Unit 5_腦機介面(許巍嚴) :作業成績 50%、報告50%
| 週次 | 主題 |
|---|---|
| 第 1 週 | 統一9/2(二)9:00課程說明 |
| 第 2 週 | Unit 1_ROS程式設計基礎(陳建志): 單元主題:ROS introduction 課程內容:ROS introduction, Raspberry pi settings, VirtualBox and Linux Image |
| 第 3 週 | Unit 1_ROS程式設計基礎(陳建志): 單元主題:ROS程式開發及ROS通訊 課程內容:ROS file systems, 1st ROS program, ROS communications, ROS launch |
| 第 4 週 | Unit 1_ROS程式設計基礎(陳建志): 單元主題:ROS parameters及專案開發 課程內容:ROS parameters, Open source packages, Multi-device communications, Image backup |
| 第 5 週 | Unit 2_Mathemetics for Machine Learning(馬清文) : 1. algebra foundations such as equations, functions, and graphs; differential calculus such as derivatives and optimization; |
| 第 6 週 | Unit 2_Mathemetics for Machine Learning(馬清文) : linear algebra such as vector-matrix multiplication and matrix decomposition; |
| 第 7 週 | Unit 2_Mathemetics for Machine Learning(馬清文) : statistics, probability and basic information theory. |
| 第 8 週 | Unit 3_Math and Deep Learning(魏澤人): 單元主題:Math related to AI 課程內容:Including optimization theory, probability, graph theory, and differential equations. |
| 第 9 週 | Unit 3_Math and Deep Learning(魏澤人): 單元主題:AI tools for Math 課程內容:Using AI to solve math problems. |
| 第 10 週 | Unit 3_Math and Deep Learning(魏澤人): 單元主題:Theoretical tools 課程內容:Math foundations to understand theory of AI and deep learning. |
| 第 11 週 | Unit4_衛星影像成像原理應用介紹(許志仲) 課程內容:多光譜與高光譜影像成像原理與應用之介紹 |
| 第 12 週 | Unit4_Invited Talk(許志仲) 課程內容:Invited Talk |
| 第 13 週 | Unit4_Invited Talk(許志仲) 課程內容:Invited Talk |
| 第 14 週 | Unit 5_腦機介面(許巍嚴) : 單元主題:腦機介面概念 課程內容:腦機介面概念 |
| 第 15 週 | Unit 5_腦機介面(許巍嚴) : 單元主題:腦機介面技術 課程內容:腦機介面技術 |
| 第 16 週 | Unit 5_腦機介面(許巍嚴) : 單元主題:腦機介面應用 課程內容:腦機介面應用 |
Unit 1_ROS程式設計基礎(陳建志): 課程講義 "Learning Robotics Using Python", 作者: Lentin Joseph, 原文出版社:Packt Pub Ltd, 出版日期:2015/05/30, ISBN:9781783287536、 "Mastering ROS for Robotics Programming", 作者: Lentin Joseph, 原文出版社:Packt Pub Ltd, 出版日期:2015/12/31, ISBN:9781783551798 Unit 2_Mathmetics for Machine Learning(馬清文): 1. Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. MATHEMATICS FOR MACHINE LEARNING. Cambridge University Press, 2020 2. Goodfellow and Yoshua Bengio and Aaron Courville. Deep Learning. Chapter 2,3,4,5. MIT Press, 2016 Unit 3_Math and Deep Learning(魏澤人):N/A Unit 4_衛星影像處理(許志仲):N/A Unit 5_腦機介面(許巍嚴) :自備教材、相關論文