課程資訊
課程名稱
智慧機器人應用與實作
Application and Practical of Intelligent Robot 
開課學期
114-1 
授課對象
工學院  機械工程學研究所  
授課教師
郭重顯 
課號
ME5065 
課程識別碼
522 U6420 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期五2,3,4(9:10~12:10) 
上課地點
機械104 
備註
實作地點為機械B119室(機器人實作實驗室)。與何世池合授
總人數上限:30人 
 
課程簡介影片
 
核心能力關聯
核心能力與課程規劃關聯圖
課程大綱
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課程概述

The course entitled “Application and Practical of Intelligent Robot” is a project-based learning (PBL) course, and it aims at cultivating the students with the capability of utilizing the collaborative robot (TM-5) for industry smart automation applications. The composition of this course consists of 2 hours lecture talk and 2 hours hands-on practice. The lecture topics are arranged as follows:
1. Introduction of collaborative robots and their industrial applications
2. Introduction of TM-5 collaborative robot and TM flow HMI
3. 2D robotic computer vision (Eye-in-hand / Eye-to-hand)
4. Machine learning with TM AI+
5. Human-Machine Interface (I) - TMCraft Shell
6. Presentation and review on final project proposal (team)
7. Human-Machine Interface (II) - Python
8. Applications of Generative AI with Robotics (I)
9. Applications of Generative AI with Robotics (II)
10. Human-Machine Interaction (III) - User Interface with NLP/ LLM
11. Applications of Generative AI with Robotics (III)
 

課程目標
The students are capable of learning:
1. Popular collaborative robots (TM-5)
2. Operative software and tools (TMflow HMI and TMCraft Shell )
3. Entry level AI programming and tools (TM AI+ and Python)
4. Robot operating system (ROS 2)
5. Generative AI with Robotics 
課程要求
Python programming skill 
預期每週課前或/與課後學習時數
3 to 6 hours, depending on topics and individuals 
Office Hours
每週一 09:00~12:50 
指定閱讀
Handouts  
參考書目
Conference and journal papers; open source codes and documents 
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Class attendance and participation 
10% 
Lectures and labs are counted 
2. 
Final project proposal presentation 
10% 
Presentation and review on final project proposal (team) 
3. 
Midterm exam 
25% 
Examination on TM robot operation for a specific task (team) 
4. 
Lab exercise achievement 
20% 
All lab topics are counted 
5. 
Final project report 
35% 
Presentation and review on final project outcome and achievement (team) 
  1. 本校尚無訂定 A+ 比例上限。
  2. 本校採用等第制評定成績,學生成績評量辦法中的百分制分數區間與單科成績對照表僅供參考,授課教師可依等第定義調整分數區間。詳見學習評量專區 (連結)。
 
針對學生困難提供學生調整方式
 
上課形式
以錄影輔助, 提供學生彈性出席課程方式
作業繳交方式
延長作業繳交期限, 學生與授課老師協議改以其他形式呈現
考試形式
延後期末考試日期(時間)
其他
由師生雙方議定
課程進度
週次
日期
單元主題
第1週
9/5  Introduction of collaborative robots and their industrial applications 
第2週
9/12  Introduction of TM-5 collaborative robot and TM flow HMI 
第3週
9/19  2D robotic computer vision (Eye-in-hand / Eye-to-hand) 
第4週
9/26  Machine learning with TM AI+ 
第5週
10/3  Human-Machine Interface (I) - TMCraft Shell 
第6週
10/10  National Day 
第7週
10/17  Presentation and review on final project proposal (team) 
第8週
10/24  Taiwan Retrocession and Battle of Guningtou Victory Memorial Day 
第9週
10/31  Midterm exam: examination on TM robot operation for a specific task (team)
 
第10週
11/7  Human-Machine Interface (II) - Python 
第11週
11/14  Applications of Generative AI with Robotics (I) 
第12週
11/21  Anniversary Sports Day 
第13週
11/28  Applications of Generative AI with Robotics (II) 
第14週
12/5  Human-Machine Interaction (III) - User Interface with NLP/ LLM 
第15週
12/12  Applications of Generative AI with Robotics (III) 
第16週
12/19  Presentation and review on final project (team)