AUTONAVx: Autonomous Navigation for Flying Robots

TUMx

In this course, we will introduce the basic concepts for autonomous navigation with quadrotors, including topics such as probabilistic state estimation, linear control, and path planning.

About this Course

*Note - This is an Archived course*

This is a past/archived course. At this time, you can only explore this course in a self-paced fashion. Certain features of this course may not be active, but many people enjoy watching the videos and working with the materials. Make sure to check for reruns of this course. 

In recent years, flying robots such as miniature helicopters or quadrotors have received a large gain in popularity. Potential applications range from aerial filming over remote visual inspection to automatic 3D reconstruction of buildings. Navigating a quadrotor manually requires a skilled pilot and constant concentration. Therefore, there is a strong scientific interest to develop solutions that enable quadrotors to fly autonomously and without constant human supervision. This is a challenging research problem because the payload of a quadrotor is uttermost constrained and so both the quality of the onboard sensors and the available computing power is strongly limited.

In this course, we will introduce the basic concepts for autonomous navigation for quadrotors including topics such as probabilistic state estimation, linear control, and path planning. You will learn how to infer the position of the quadrotor from its sensor readings, how to navigate along a series of waypoints, and how to plan collision free trajectories. The course consists of a series of weekly lecture videos that we be interleaved by interactive quizzes and hands-on programming tasks. The programming exercises will require you to write small code snippets in Python to make a quadrotor fly in simulation.

This course is intended for graduate students in computer science, electrical engineering or mechanical engineering. The course is based on the TUM lecture “Visual Navigation for Flying Robots” which received the TUM TeachInf best lecture award in 2012 and 2013. The course website from last year (including lecture videos and course syllabus) can be found here: http://vision.in.tum.de/teaching/ss2013/visnav2013

Course Staff

  • Jürgen Sturm

    Jürgen Sturm is a postdoctoral researcher in the Computer Vision group at the Technische Universität München. His major research interests lie in dense localization and 3D reconstruction for micro aerial vehicles. In 2011, he obtained his PhD from the Autonomous Intelligent Systems lab headed by Prof. Wolfram Burgard at the University of Freiburg. He won several awards including the ECCAI best dissertation award in 2011 and the TUM Teach Inf best lecture award for his course "Visual Navigation for Flying Robots" in 2012 and 2013.

  • Daniel Cremers

    Daniel Cremers received Bachelor degrees in Mathematics (1994) and Physics (1994), and a Master's degree in Theoretical Physics (1997) from the University of Heidelberg. In 2002 he obtained a PhD in Computer Science from the University of Mannheim, Germany. Subsequently he spent two years as a postdoctoral researcher at the University of California at Los Angeles (UCLA) and one year as a permanent researcher at Siemens Corporate Research in Princeton, NJ. From 2005 until 2009 he was associate professor at the University of Bonn, Germany. Since 2009 he holds the chair for Computer Vision and Pattern Recognition at the Technische Universität München. His publications received several awards, including the award of Best Paper of the Year 2003 by the Int. Pattern Recognition Society and the 2005 UCLA Chancellor's Award for Postdoctoral Research. In December 2010 the magazine Capital listed Prof. Cremers among "Germany's Top 40 Researchers Below 40".

  • Christian Kerl

    Christian Kerl is a PhD student in the Computer Vision group at the Technische Universität München. His main research interests, are visual SLAM and 3D reconstruction using RGB-D cameras, either mounted on a quadrotor or handheld. In 2012, he obtained his Master's degree in Robotics from the Technische Universität München.

  • Julian Tatsch

    Julian Tatsch is a master student in computer science at the Technische Universität München. He supports the creation of the interactive exercises.

  • Jonas Jelten

    Jonas Jelten is a bachelor student in computer science at the Technische Universität München. He supports the creation of the interactive exercises.

  • Benjamin Strobel

    Benjamin Strobel is a master student in computer science at the Technische Universität München. He is in charge of the transcriptions of the video lectures and helped with the setup instructions for the real Parrot AR.Drone.

会期:
  • 2014年5月06日, 8 星期
介绍:
  • 免费:
  • 收费:
  • 证书:
  • MOOC:
  • 视频讲座:
  • 音频讲座:
  • Email-课程:
  • 语言: 英语 Gb

反馈

目前这个课程还没有反馈。您想要留第一个反馈吗?

请注册, 为了写反馈

Show?id=n3eliycplgk&bids=695438
NVIDIA
还有这个题目的:
Eth_mobroboto_262x136 AMRx: Autonomous Mobile Robots
Introduction to Autonomous Mobile Robots – basic concepts and algorithms for...
Saas_verified CS169.2x: Software as a Service
CS169.2x teaches sophisticated SaaS+Agile skills, such as working with legacy...
Cs169.1x_262x136_verified_0 CS169.1x: Engineering Software as a Service
CS169.1x teaches the fundamentals of software engineering using Agile techniques...
Cs188.1x-listing-banner CS188.1x: Artificial Intelligence
CS188.1x is an online adaptation of the first half of UC Berkeley's upper division...
7-349s10 From Molecules to Behavior: Synaptic Neurophysiology
Like transistors in a computer, synapses perform complex computations and connect...
还有标题«计算机科学»:
795999aa-6a59-42ac-ba38-feec9ec2be7f-95fe84bc13fd.small Penetration Testing - Exploitation
Learn exploitation phase of penetration testing, including the foundations of...
2cc77eb5-e1b3-4d57-87f6-bf071804e2ab-1d34e01a3545.small Penetration Testing - Post Exploitation
Learn post-exploitation phases of penetration testing, including Owning, Pivoting...
7ca98c09-a207-40c7-8a84-b9c48ecdf920-f25c990d1f5f.small Cloud Computing Engineering and Management
Learn methods for managing cloud computing projects and build an understanding...
9395b535-1fa7-4ed4-9fd8-98b86ba682d9-98e1ff5caeec.small UX Research
In this MOOC you will learn how to connect with users at every step of a digital...
61be438f-28b9-4339-9437-21c34b3c3dd6-e9ecfcecaf58.small UX Prototyping
Become a prototyping virtuoso! Master the ability to propel your creative team...
还有edX:
795999aa-6a59-42ac-ba38-feec9ec2be7f-95fe84bc13fd.small Penetration Testing - Exploitation
Learn exploitation phase of penetration testing, including the foundations of...
66a5462a-1a44-4010-b419-d313d9218090-d8d4d0d32eba.small Statistical Predictive Modelling and Applications
Learn how to apply statistical modelling techniques to real-world business scenarios...
F8d26e31-a9ea-4891-8e4d-ccf3be0e10f2-af109b42c4db.small Project Finance: Funding Projects Successfully
Learn the key strategies used by project managers to generate crucial funding...
1e7ac3ee-58cb-47dd-b887-b845fca21a82-a170765fa771.small Efficient HVAC Systems
Learn how to decide on efficient combinations of energy conversion systems and...
89db1e57-5bf9-4f4e-82a1-9cdb09c6846e-f6e1130fc6b5.small Business success in the screen industries: how to pitch your script and self-produce
Learn how to network in the creative industries, how pitch your film to a producer...

© 2013-2019