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課程名稱 |
機器人知覺與學習
ROBOT PERCEPTION AND LEARNING |
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開課學期 |
98-1 |
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授課對象 |
電機資訊學院 資訊網路與多媒體研究所 |
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授課教師 |
王傑智 |
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課號 |
CSIE5117 |
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課程識別碼 |
922EU3430 |
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班次 |
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學分 |
3 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期三6,7,8(13:20~16:20) |
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上課地點 |
資110 |
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備註 |
本課程以英語授課。
限學士班四年級以上
總人數上限：30人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/981pal |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
Robotics has achieved its great success to date in the world of industrial manufacturing. Robot arms, or manipulators, comprise a 2 billion dollar industry. However, these commercial robots/manipulators suffer from a fundamental disadvantage: lack of mobility. This course will cover both science and systems that allows a mobile robot to move through a real-world environment to perform its tasks, including action, perception, planning and learning. |
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課程目標 |
The topics that will be discussed include:
The Action-Perception-Cognition Loop,
Locomotion,
Mobile Robot Kinematics,
Dynamics and Control,
Uncertainty,
Sensors and Sensing,
Localization (EKF, Markov),
Mapping (Feature-based, Grid-based approaches),
Object & Activity Recognition,
Path Planning,
Cooperative Mobile Robotics,and
Learning. |
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課程要求 |
1. Familiarity with software development in Matlab, C or C++ will be essential/helpful for this course.
2. But the most important prerequisite will be creativity and enthusiasm, and a desire to explore.
3. The course load is “heavy”. Think twice if you want to take this course.
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預期每週課後學習時數 |
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Office Hours |
另約時間 |
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指定閱讀 |
Introduction to Autonomous Mobile Robots by Roland Siegwart and Illah R.
Nourbakhsh, the MIT press, April 2004, ISBN: 0-262-19502
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參考書目 |
Springer Handbook of Robotics by Siciliano, Bruno; Khatib, Oussama (Eds.),
the Springer press, June 2008, ISBN: 978-3-540-23957-4. Online version available.
The Robotics Primer by Maja J. Mataric , the MIT press, September 2007, ISBN:
0-262-63354-X
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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Week 1 |
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Introduction |
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Week 2 |
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Sensors for Perception |
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Week 3 |
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Range Sensors and Processing |
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Week 4 |
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Scan Matching and Registration (ICCV 2005 short course: 3D Scan Matching and Registration, http://www.cs.princeton.edu/~bjbrown/iccv05_course/) |
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Week 5 |
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Cameras |
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Week 6 |
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Midterm Exam I |
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Week 7 |
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Uncertainty |
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Week 8 |
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Localization |
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Week 9 |
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Mapping |
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Week 10 |
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Tracking |
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Week 11 |
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Object Recognition |
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Week 12 |
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Midterm Exam II |
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Week 13 |
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No Class |
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Week 14 |
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Face Detection and Alignment, Hand Posture Recognition |
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Week 15 |
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Kinematics of Manipulation and Locomotion, Control and Architecture |
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Week 16 |
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To be announced |
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Week 17 |
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Planning and Obstacle Avoidance |
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Week 18 |
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Final Competition |
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Week 19 |
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Final Competition |
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