Ubuntu laptop terminal interface with hands operating keyboard, Duckiebot and duckies out of focus in foreground

“Self-Driving Cars with Duckietown” MOOC starting soon

Join the first hardware based MOOC about autonomy on edX!

Are you curious about robotics, self-driving cars, and want an opportunity to build and program your own? Set to start on March 22nd, “Self-Driving Cars with Duckietown” is a hands-on introduction to vehicle autonomy, and the first ever self-driving cars MOOC with a hardware track!

Designed for university-level students and professionals, this course is brought to you by the Swiss Federal Institute of Technology in Zurich (ETHZ), in collaboration with the University of Montreal, the Duckietown Foundation, and the Toyota Technological Institute at Chicago.

Learning autonomy requires a fundamentally different approach when compared to other computer science and engineering disciplines. Autonomy is inherently multi-disciplinary, and mastering it requires expertise in domains ranging from fundamental mathematics to practical machine-learning skills.

This course will explore the theory and implementation of model- and data-driven approaches for making a model self-driving car drive autonomously in an urban environment, while detecting and avoiding pedestrians (rubber duckies)!

In this course you will learn, hands-on, introductory elements of:

  • computer vision
  • robot operations 
  • ROS, Docker, Python, Ubuntu
  • autonomous behaviors
  • modelling and control
  • localization
  • planning
  • object detection and avoidance
  • reinforcement learning.

The Duckietown robotic ecosystem was created at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) in 2016 and is now used in over 90 universities worldwide.

“The Duckietown educational platform provides a hands-on, scaled down, accessible version of real world autonomous systems.” said Emilio Frazzoli, Professor of Dynamic Systems and Control, ETH Zurich, “Integrating NVIDIA’s Jetson Nano power in Duckietown enables unprecedented access to state-of-the-art compute solutions for learning autonomy.”

This massive online open course will be have a hands-on learning approach using, for the hardware track, real robots. You will learn how autonomous vehicles make their own decisions, going from theory to implementation, deployment in simulation as well as on the new NVIDIA Jetson Nano powered Duckiebots.

“The new NVIDIA Jetson Nano 2GB is the ultimate starter AI computer for educators and students to teach and learn AI at an incredibly affordable price.” said Deepu Talla, Vice President and General Manager of Edge Computing at NVIDIA. “Duckietown and its edX MOOC are leveraging Jetson to take hands-on experimentation and understanding of AI and autonomous machines to the next level.”

The Duckiebot MOOC Founder’s edition kits are available worldwide, and thanks to OKdo, are now available with free shipping in the United States and in Asia!

“I’m thrilled that ETH, with UMontreal, the Duckietown Foundation, and the Toyota Technological Institute in Chicago, are collaborating to bring this course in self-driving cars and robotics to the 35 million learners on edX. This emerging technology has the potential to completely change the way we live and travel, and the course provides a unique opportunity to get in on the ground floor of understanding and using the technology powering autonomous vehicles,” said Anant Agarwal, edX CEO and Founder, and MIT Professor.

Enroll now and don’t miss the chance to join in the first vehicle autonomy MOOC with hands-on learning!

The “Self-Driving cars with Duckietown” hands-on Massive Open Online Course on edX

"Self-Driving Cars with Duckietown" hands-on MOOC on edX

We are launching a massive open online course (MOOC): “Self-Driving Cars with Duckietown” on edX, and it is free to attend! 

This course is made possible thanks to the support of the Swiss Federal Institute of Technology in Zurich (ETHZ), in collaboration with the University of Montreal, the Duckietown Foundation, and the Toyota Technological Institute at Chicago.

This course combines remote and hands-on learning with real-world robots. It is offered on edX, the trusted platform for learning, and it is now open for enrollment

Learning activities will support the use of Jetson Nano equipped Duckiebots, powered by NVIDIA.

Learning autonomy

Participants will engage in software and hardware hands-on learning experiences, with focus on overcoming the challenges of deploying autonomous robots in the real world.

This course will explore the theory and implementation of model- and data-driven approaches for making a model self-driving car drive autonomously in an urban environment.

Pedestrian detection

MOOC Factsheet

  • Name: Self-driving cars with Duckietown
  • Start: March 2021
  • Platform: edX
  • Cost: free to attend

Prerequisites

  • Basic Linux, Python, Git
  • Elements of linear algebra, probability, calculus
  • Elements of kinematics, dynamics
  • Computer with native Ubuntu installation

What you will learn​

  • Computer Vision
  • Robot operations
  • Object Detection
  • Localization, planning and control
  • Reinforcement Learning

Why Self-driving cars with Duckietown?

Teaching autonomy requires a fundamentally different approach when compared to other computer science and engineering disciplines, because it is multi-disciplinaryMastering it requires expertise in domains ranging from fundamental mathematics to practical machine-learning skills.

Robot Perception 

Robots operate in the real world, and theory and practice often do not play well togetherThere are many hardware platforms and software tools, each with its own strengths and weaknesses. It is not always clear what tools are worth investing time in mastering, and how these skills will generalize to different platforms. 

Duckiebot Detection

Learning through challenges

Progressing through behaviors of increasing complexity, participants uncover concepts and tools that address the limitations of previous approaches. This allows to get Duckiebots to actually do things, while gradually re-iterating concepts through various technical frameworks. Simulation and real-world experiments will be performed using a Python, ROS, and Docker based software stack.

Robot Planning

(Hidden) This line and everything under this line are hidden

This course combines remote and hands-on learning with real-world robots.

It is offered on edX, the trusted platform for learning, and it is now open for enrollment.

Learning activities will support the use of NVIDIA Jetson Nano powered Duckiebots.

Montreal 2017

Duckietown at Université de Montréal 2017

Prof Liam Paull debuted Duckietown at UdeM in the fall 2017 semester. There were 13 students and two teaching assistants. The class culminated in an Expo, where members of the community were invited to learn about the accomplishments of the class. 

RPI 2016 Course Projects

Here are some video’s from John Wen and Jeff Trinkle’s course projects from the algorithmic robotics in 2016 at Rennselaer Polytechnic Institute.

Duckietown Summer School 2018, Taiwan

2018 AI DRIVING OLYMPICS
AI駕駛訓練課程

暑期學校

一起進入AI Driving/Robotics領域

培訓課程為介紹性課程,對象為對AI Driving/Robotics有興趣的大學生,課程目標為培育人才進入AI Driving/Robotics領域,能了解自走車基本原理,並完成此競賽之基本任務。已有相關專業的學生或團對亦可直接參與競賽,不一定需要參加此課程。

做中學的課程內容

本課程以實作為主,深入淺出

  • 2018/08/06: 人工智慧自走車與開發環境 (Raspberry Pi3、Ubuntu作業系統實作)
  • 2018/08/07: AI Computing(基礎Python語言、電腦視覺OpenCV、深度學習套件)
  • 2018/08/08: 機器人作業系統Robot Operation System (ROS)與AI Hardware
  • 2018/08/09: AI Driving Olympics參賽介紹(Docker容器技術、虛擬環境、雲端計算)
  • 2018/08/10: AI Driving/Robotics 論壇

與教授實驗室有約

本課程希望與AI Driving/Robotics教授實驗室連結,將安排與教授或實驗室學長姐用餐交流,希望同學將來進入實驗室進行深入研究。

正式的微學分課程(2學分)

本課程為交大NCTU ICT正式課程,交大大學部同學將有2學分,本課程將提供自走小鴨車機器人,在課程結束後收回,參與課程同學須自備筆記型電腦,本課程評量方式將根據實作模組完成度,以及課程AI Driving Olympics計分(自主駕駛平穩、安全係數等),感謝NCTU ICT及其他單位支持,本課程不收費。

加入暑期學校,進入AIDO-國際AI駕駛競賽!

國際頂尖機器學習研討會-NIPS (Conference on Neural Information Processing Systems),將舉行國際AI駕駛競賽!Duckietown與5間頂尖大學、2間國際企業協同主辦競賽。加入暑期學校,你將擁有第一手的資訊與經驗!

點擊此處查看關於AIDO詳細資訊!

交大團隊


交大指導委員會(NCTU Steering Committee)

陳俊勳副校長
陳信宏副校長
電機學院唐震寰院長
資訊學院、工學院院長(邀請中)
人工智慧普適研究中心曾煜棋主任


交大執行工作小組(NCTU WORKING TEAM)

電機系 王學誠教授
電子所 賴伯承教授
資工系 陳永昇教授
科法所 莊弘鈺教授

電機系 帥宏翰教授
電控所 楊谷洋教授
機械系 蔡佳宏教授
建築所 許倍銜教授

交大學生工作團隊

呂承龍 鴨子城市長
陳品維 鴨子城執行長

曹立武
蔡承運
陳鼎元
夏子翔
賴煒承
李聖誠
李宗儒
楊翰祥
沈育嘉
李易霖
劉蓁

歐彥宏 鴨子城硬體長
賴德強 鴨子城執行委員

張博凱
高熙鈞
沈衍薰
黃成漢
楊凱翔
陳瀚仲
胡哲綸
許瑋哲
許瑋庭
林沛羽

課程時間

贊助單位

聯絡我們


想知道更多資訊,利用下列資訊與我們聯絡。

新竹市東區 大學路1001號 工五627
臺灣 30010, ROC
歐彥宏
allen.eed02@g2.nctu.edu.tw

關於競賽(隱藏中invisible,預覽看不到)

競賽介紹:

受到機器學習頂級研討會NIPS的肯定,The AI-Driving Olympics 人工智慧駕駛競賽 將於世界五所頂尖大學舉辦。國立交通大學將成為台灣唯一競賽場地。機器學習為現今最重要、並正在如火如荼發展的科技之一。此競賽的目的,為探討在機器學習如何能解決複雜機器人系統中的主要任務與次要任務。此競賽將由若干不同項目所組成,這些項目將對應到各項日漸複雜的車輛駕駛表現,從最基本的道路行駛到更加複雜的、“認知性”的任務。此競賽的參與者將由世界各地,經由網路連線到台灣的全自動競賽場地,在場地中實現該隊伍的演算法,並試圖再一次次的試驗中,更加精進自己的表現。此競賽將以麻省理工研發之模擬城鎮 Duckietown 鴨子城(右圖) 為基礎,進行建構。

競賽規劃:

  • 軟體模擬: 在資格賽的部分,我們將要求參賽者先於電腦模擬的環境中測試該隊伍的演算法。
  • 實體場域: 我們將於國立交通大學建構實體競技場,讓演算法不只是空談而能實際運作在真實的機器人上。
  • 五大名校: 此競賽將由蘇黎世聯邦理工學院、國立交通大學、蒙特婁大學、喬治亞州理工學院、北京清華大學五校聯合舉辦。
  • 企業雙雄: 此競賽將與nuTonomy自動駕駛公司以及amazon亞馬遜公司合作,使企業之技術與能力能與學界合作。

預期成果

  • 先進技術研發: 藉由舉辦此比賽,刺激國內機器學習相關科技進展,提升我國於先進技術之研發。
  • 提高國際能見度: 參賽選手將透過網路連線至台灣的場地,各地之選手便能認識台灣科技之能耐。並讓台灣人材被國際看見。

Duckietown @ NCTU is hosting the Summer School 2018 on August 6-10 in Hsinchu, Taiwan. The hands-on classes target college-level students and robotics enthusiasts, and cover introductory materials and baseline solutions to the AI Driving Olympics competition. The summer school in 2018 includes professors from Taiwan, Korea and Indonesia, and more than 100 students from 10 universities, serving as the hub to bring together teaching and learning community for autonomy and robotics education.

(隱藏中invisible,預覽看不到)

電機系 王學誠教授

電機系 帥宏翰教授

電子所 賴伯承教授

電控所 楊谷洋教授

資工系 陳永昇教授

機械系 蔡佳宏教授

科法所 莊弘鈺教授

建築所 許倍銜教授

呂承龍
鴨子城市長

歐彥宏
鴨子城硬體長

陳品維
鴨子城執行長

賴德強
鴨子城執行委員

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2018 AI DRIVING OLYMPICS
AI駕駛競技大賽(隱藏中)

黃色小鴨中的先進科技

Duckietown Summer School 2017, Taiwan

Objective 

The first Duckietown Summer School aims at training potential instructors and teaching assistants in future Duckietown courses. Since Duckietown is project-based learning, teaching assistants and mentors are one of the most important resources to make a successful Duckietown course. We believe that such training is a valuable learning experience for students’ skills of problem solving, team work, and leadership. We are happy to have individuals from Korea, Indonesia, and Taiwan in the first Duckietown Summer School. All materials are available as open source, and the hope is that others in the community will adopt the platform for education and research. The first Duckietown Summer School held in National Chiao Tung University, Hsinchu, Taiwan on July 17-19, 2017.

Program 
The first Duckietown Summer School is held in National Chiao Tung University, Hsinchu, Taiwan on July 17-19, 2017. There are 8 sections, and the detail of each section is here .

Professional Training The 3-day course includes both hardware, such as Duckiebot assembly, soldering of PWM, 3D printing, as well as software developments: Robot Operation System (ROS), Python, Jupyter Notebook, and OpenCV. We will also cover the principles and processing steps of autonomous lane following.

Learning by Doing – Each section will include a 15-20 minute lecture, followed by hand-on section to finish a few specific tasks.

Evaluation – Each participant needs to finish the tasks in each section, and forms small group for final presentation (5 minute spotlight and a live demo or video.