流水號
29889
課號
ME5075
課程識別碼
522 U6530
無分班
- 3 學分
選修
機械工程學系 / 機械工程學研究所
機械工程學系
機械工程學研究所
選修- 郭重顯
- 搜尋教師開設的課程
工學院 機械工程學系
- 五 2, 3, 4
工綜205
3 類登記
修課總人數 30 人
本校 30 人
無領域專長
- 中文授課
- NTU COOL
- 核心能力與課程規劃關聯圖
- 備註尚需另排時段作兩小時的實作，實作地點為工綜B38室(機械手臂教室)。與林沛群、何世池合授
- 修課限制
限本系所學生(含輔系、雙修生)
本校選課狀況
載入中- 課程概述本課程的內容包括以下主題： 1. 自主移動機器人(AMR)簡介 2. 機器人作業系統 3. 運動學與輪軸里程計 4. 感測融合 5. 定位與建置地圖 6. 路徑規劃 7. 障礙物偵測與避障 8. TM Flow視覺機器手臂取放 9. TM 機器手與AMR之整合應用 10. PBL I：場域地圖建置與AMR定位 11. PBL II：路徑規劃與自主導航 12. PBL III：自主物件遞送與取放 The content of this course consists of the following topics: 1. Introduction to autonomous mobile robots (AMR) 2. Robot operating system (ROS) 3. Kinematics and wheel odometry 4. Sensor fusion 5. Localization and mapping 6. Path planning 7. Obstacle detection and avoidance 8. Vison-based object picking with TM Flow 9. Integrated applications of TM robot and AMR 10. PBL I: Mapping and AMR localization 11. PBL II: Path planning and autonomous navigation 12. PBL III: Autonomous object delivery with performing pick-and-place
- 課程目標本課程採以專案導向學習（PBL）之設計，其目的在於提供學生學習自主移動機器人之運動學和輪軸測距、感測融合、定位和建圖、路徑規劃以及障礙物偵測和避障的基礎學理。此外，本課程也介紹機器人作業系統（ROS）和TM Flow，以更有效率方式學習結合AMR 及6軸TM機器人之實務應用。 此一課程也安排了建圖及AMR 定位、路徑規劃和自主導航、以及執行自主物件遞送與取放等三個 PBL 主題，以提升學生在AMR之實作技術以及實務問題解決的能力。 This course is developed as a project-based learning (PBL) course. The students are capable of learning the fundamentals of kinematics and wheel odometry, sensor fusion, localization and mapping, path planning, and obstacle detection and avoidance with the autonomous mobile robots. Moreover, this course also introduces robot operating system (ROS) and TM flow to efficiently learn the practical implementation aspects of an AMR with 6-axis TM robot. Three PBL topics, including mapping and AMR localization, path planning and autonomous navigation, and autonomous object delivery with performing pick-and-place, are arranged to help to improve the hands-on skills and problem-solving capabilities.
- 課程要求Python programming skill
- 預期每週課後學習時數3 to 6 hours, depending on topics
- Office Hour
星期一 09:00 - 23:50 - 指定閱讀課程教材 Handouts
- 參考書目期刊論文，會議論文，GitHub Journal papers, conference proceedings, GitHub
- 評量方式
10% Class attendance and participation 10%
Lectures and labs are counted
25% Midterm exam
Mission competition with coding (team)
10% Final project proposal presentation
Presentation and review on final project proposal (team)
30% Final project report
Presentation and review on final project outcome and achievement (team)
25% Lab exercise achievement
All lab topics are counted
- 針對學生困難提供學生調整方式
調整方式 說明 上課形式 以錄影輔助
作業繳交方式 延長作業繳交期限
考試形式 延後期末考試日期(時間)
- 課程進度
2/23第 1 週 2/23 Introduction to autonomous mobile robots (AMR) 3/1第 2 週 3/1 Robot operating system (ROS) 3/8第 3 週 3/8 Sensor fusion, localization and mapping 3/15第 4 週 3/15 Path planning 3/22第 5 週 3/22 Kinematics and wheel odometry (Prof. Pei-Chun Lin) 3/29第 6 週 3/29 Obstacle detection and avoidance 4/12第 8 週 4/12 Proposal of final project 4/19第 9 週 4/19 Midterm exam (mission competition) 4/26第 10 週 4/26 Vison-based object picking with TM Flow 5/3第 11 週 5/3 Assembly and control of a 3-DOF arm and a gripper on an AMR 5/10第 12 週 5/10 Invited talk: ITRI robots and industrial applications 5/17第 13 週 5/17 PBL I: Mapping and AMR localization 5/24第 14 週 5/24 PBL II: Path planning and autonomous navigation 5/31第 15 週 5/31 PBL III: Autonomous object delivery with performing pick-and-place 6/7第 16 週 6/7 Final project presentation