課程資訊
課程名稱
系統專題研究-物聯網中介軟體設計
System Design Topic - Design for IoT Middleware 
開課學期
113-1 
授課對象
重點科技研究學院  精準健康博士學位學程  
授課教師
施吉昇 
課號
CSIE5317 
課程識別碼
922 U4330 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期二7,8,9(14:20~17:20) 
上課地點
資105 
備註
總人數上限:50人 
 
課程簡介影片
 
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課程概述

此課程將以實際操作為主的方式進行,學生將透過研讀一個物聯網中介軟體的原始碼學習系統中介軟體的設計方法,並以此一中介軟體作為實作的平台,讓學生可以開發中介軟系統與元件。此外,本課程將搭配與自駕車系統軟體設計與實作,與資料處理。

The course is designed for senior and graduate students in Computer Science major to learn the design philosophy, practice and research challenges for Programming IoT Middleware and autonomous systems. 

課程目標
The requirements of applications for Internet-of-Things are highly domain dependent. The applications require to use services executed on heterogeneous platforms, including hardware platforms and communication networks. Middleware for IoT provides several features, including services composition, service management, device management, and application management. With the middleware, the complexity and overhead of developing IoT application can be reduced and the performance can be enhanced. In this semester, the course has selected autonomous system, in particular, self-driving vehicle, as the IoT system to study. 
課程要求
Course participate, programming assignment and final project. 
預期每週課後學習時數
 
Office Hours
每週五 09:30~11:00 備註: Office Hour (1) is only valid after Oct. 12, 2024. Appointments can be made by email before Oct. 12, 2024. 
指定閱讀
“Probabilistic robotics.”, by Thrun, Sebastian, Wolfram Burgard, and Dieter Fox., Cambridge:
MIT press, 2000. 
參考書目
“Introduction to Embedded Systems, A Cyber-Physical Systems Approach” by Edward A. Lee
and Sanjit A. Seshia, 2nd Edition, 2017. Its online version is freely available at
http://leeseshia.org.
“Distributed Systems: Principles and paradigms.” Hence, it is recommended to own this book
for your reference in the class and/or for the future.
“Probabilistic robotics.”, by Thrun, Sebastian, Wolfram Burgard, and Dieter Fox., Cambridge:
MIT press, 2000. 
評量方式
(僅供參考)
   
針對學生困難提供學生調整方式
 
上課形式
以錄音輔助, 以錄影輔助
作業繳交方式
延長作業繳交期限, 書面報告取代口頭報告
考試形式
書面(口頭)報告取代考試
其他
課程進度
週次
日期
單元主題
Week 1
9/3/2024  Syllabus and Introduction for IoT and Middleware 
Week 2
09/10/24  IoT Application Requirements and Use Case: Intelligent Transportation 
Week 3
09/17/24  No Class (Holiday for Moon Festival) 
Week 4
09/24/24  Middleware for Self-Driving - Autoware
Lab 1: Software Deployment for Autoware and ROS2, Simulation. 
Week 5
10/01/24  Message Exchange on Vehicle: CAN and Pub/Sub model, Robotic Operating Systems (ROS)
Lab 2-1: Camera-Lidar Calibration and Object Detection (2 Hours) 
Week 6
10/08/24  Hardware Platforms: MCU-based platforms and CPU-based platforms, Sensors for Autonomous (1 Hour) 
Week 7
10/15/24  Probabilistic Robotics (2 Hours)
Lab 2-2: Lidar-IMU Calibration (1 Hours) 
Week 8
10/22/24  Mid-Term (In-Class) 
Week 9
10/29/24  Perception for Self-Driving Vehicle
Lab 3: Map and Localization 
Week 10
11/05/24  Perception for Self-Driving Vehicle 
Week 11
11/12/24  Navigation and localization
Lab 4: Vehicle Control 
Week 12
11/19/24  Navigation and localization 
Week 13
11/26/24  Free Space Estimation
Final Project: Waypoint Pursue and object avoidance 
Week 14
12/03/24  Planning and Advanced Driving Assistive Systems (ADAS) 
Week 15
12/10/24  Simulation and Testing for Self-Driving (Cloud Native Development for Autonomous Driving) 
Week 16
12/17/24  Final Project Demo (No Exam) 
Week 17
12/24/24  Additional and optional Final Project demo