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Robotics

Robotics,

How can robots perceive the world and their own movements so that they accomplish navigation and manipulation tasks? In this module, we will study how images and videos acquired by cameras mounted on robots are transformed into representations like features and optical flow. Such 2D representations allow us then to extract 3D information about where the camera is and in which direction the robot moves. You will come to understand how grasping objects is facilitated by the computation of 3D posing of objects and navigation can be accomplished by visual odometry and landmark-based localization.
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Rating 4.1 based on 130 ratings
Length 5 weeks
Effort 4 weeks of study, 3-5 hours/week
Starts Nov 21 (3 weeks ago)
Cost $99
From University of Pennsylvania via Coursera
Instructors Kostas Daniilidis, Jianbo Shi
Download Videos On all desktop and mobile devices
Language English
Subjects Engineering Mathematics
Tags Physical Science And Engineering Mechanical Engineering Math And Logic

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What people are saying

computer vision

Excellent Course, at the beginning I was a beginner in this topic and now I learned a lot about computer vision and visual perception.

The course is excellent is computer vision!

This course is definitely worth learning if you are interested in computer vision or robotics perceptions!

I would recommend this course to people who have some basic knowledge about computer vision (e.g.

Really good course for getting a sound foundation on geometry of computer vision.

The four week was hard ;) Good intro course for someone has no prior knowledge in Computer Vision.

All in All, a very well structured course to jump start one's career into computer vision.

Lots of cutting edge mathematical and computer vision concepts, but a serious lack of support.

It is certainly the most comprehensive course in computer vision that can be provided in a span of four weeks.

I really loved the dense collection of relevant information, this course is a great introduction to computer vision-related algorithms.Unfortunately the lecture videos are poorly edited and subtitles are inaccurate, however the slides are quite good and verbose enough to understand every topic.Assignments are quite good, however formula derivation explanations could be better.

Solid Material as an introductory course and gives glimpse on the new horizons on computer vision.

It needs very good prerequisite about computer vision.

For Computer Vision enthusiast who wants to learn about Multiple View Geometry, this is the best beginner course

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linear algebra

Some of the quiz questions are not answerable from reviewing the lecture notes and require outside knowledge of linear algebra and rotation mathematics.

You are expect to gain a general knowledge about computer vision, camera calibration, and the usage of linear algebra in computer vision.

The entire course is about linear algebra practices.

Also, computer vision, especially geometric vision is difficult to understand without a proper background in linear algebra, but the teachers' explanation was enough to fill the gaps so that even someone with only a minimalistic knowledge of linear algebra was able to consume the content.

You will be very well able to appreciate the current code base on ORB-SLAM as code does not involves derivation and this course covers all the linear algebra behind it.

It required me to go to Khan Academy and revise all about Linear Algebra + Derivatives...

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Careers

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Application Development Engineer - Fixed Robots $88k

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Applications Support Engineer - Fixed Robots $104k

Applications Support Engineer - Fixed Robots $104k

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Rating 4.1 based on 130 ratings
Length 5 weeks
Effort 4 weeks of study, 3-5 hours/week
Starts Nov 21 (3 weeks ago)
Cost $99
From University of Pennsylvania via Coursera
Instructors Kostas Daniilidis, Jianbo Shi
Download Videos On all desktop and mobile devices
Language English
Subjects Engineering Mathematics
Tags Physical Science And Engineering Mechanical Engineering Math And Logic

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