智慧系統之感知與決策(英文授課)

We focus on studying the changes in the relationship between "perception" and "decision-making" in the past, present, and future. Project-based learning is leveraged in this course. Through the course design, I hope students can learn from the past and suggest next-generation intelligent systems. We use "Intelligent Driving Systems," "Robot Manipulation," and "Robot Navigation" as the applications to verify the theories and techniques learned in the class. 本課程將透過授課與實驗並行的設計讓學生了解過去、現在與未來的智慧系統中「感知」與「決策」兩者之關係變化。希望透過本課程的設計使學生可以鑑往知來,並發想及設計新一代的智慧系統。本課程將使用「智慧型駕駛系統」、「機器人操縱」與「機器人導航」作為應用來驗證講授的理論及技術。

Programming (C/C++/Python), Linear Algebra, Probability, Computer Vision, and Machine Learning

本課程將透過授課與實驗並行的設計讓學生了解智慧系統中「感知」與「決策」。實驗部分共分為兩部份: (一) Four Computer Assignment: 透過完成作業的過程,讓學生學習如何一步步建立一個室內機器人導航系統 (Indoor Robot Navigation)。 (二) Course Project:學期第一週讓學生進行分組(2-3人一組)。每組於「智慧駕駛系統」(Intelligent Driving Systems)、「機器人導航」(Robot Navigation)、「機器人操作」(Robot Manipulation) 三領域中挑選一有興趣之研究方向。 期中、期末英文口頭報告 : - 期中:現有方法及其限制、自己的做法。 - 期末:實驗結果及分析 期末報告:總結成一篇(3-4 pages double column)的論文格式。 注意事項: 第一次上課(9/14)請務必出席,或找代理人幫你決定組別。不然如果你沒分組,我會幫你退選讓其他人加選。 **Important Note** According to the NYCU Epidemic Prevention Announcement, we will have online lectures for the first two weeks. We will meet on Google Meet on Tuesday 9/14 (1:20pm - 3:10pm) and 9/17 Friday (9am - 9:50am). The following is the link: https://meet.google.com/lookup/c26yryvrgm

Computer Assignment #1: 15% Computer Assignment #2: 15% Computer Assignment #3: 15% Computer Assignment #4: 15% Course Project: 40%  Mid and Final Presentation: 20% (10% and 10%, respectively)  Final Report: 20%

• Spatial Representation and Image Formation
• State Estimation
• Planning and Control
• Robot Navigation
• Intelligent Driving Systems
• Robot Manipulation

Slides, papers, and online resources 投影片, 論文, 線上網頁