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Opiniones y comentarios de aprendices correspondientes a Robotics: Perception por parte de Universidad de Pensilvania

4.4
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581 calificaciones
154 reseña

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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....

Principales reseñas

SK
31 de mar. de 2018

Outstanding Course! I could always count on Prof.Jianbo to crunch some of the most complex and confusing parts of the course into a much easier understandable language.

LR
31 de dic. de 2018

This is quite challenging course. So far, this is the course with the largest amount of material, I wish the class will be split into two courses.

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26 - 50 de 150 revisiones para Robotics: Perception

por Reynaldo M G

13 de feb. de 2018

This course is a tough one, the assignments are challenging. One problem with teh course is the use of english subtitles, there some errors on mathematical terms that makes more difficult to understand what is being explained (and sometimes the teachers' english is not very clear).

por Cristian D

17 de jun. de 2017

Course is unusually difficult compared to the others in the series. You'll learn plenty of stuff, though, which is useful not just in robotics itself but many other applications with a mobile camera (such as stitching panoramas taken with your phone, or producing CGI).

por Nico W

5 de feb. de 2017

Interesting material, presented well, very on-top and supportive TAs. I wish the second assignment had been the first assignment (the current first assignment is very basic and can be scrapped), so that the 4th assignment could be about implementing bundle adjustment.

por Amit K

31 de oct. de 2020

I was looking for a good course on Computer Vision which tells about its basics, Epipolar Geometry, SFM, etc. and found this module under the Robotics course. The course content was really good and explanatory. Thank You,

Amit Kumar

por Anh T

4 de nov. de 2018

Extremely challenging... took me 3 months to pass the course. It required me to go to Khan Academy and revise all about Linear Algebra + Derivatives... Especially Null Space and Jacobian ... It's challenging but it's really good.

por Charlie ( Y

9 de mar. de 2020

use the forums, and re-watch videos with the quiz pulled up

good derivations / walkthrough of spatial concepts behind the math used in various processing done in perception like SFM, working with monocular RGB data

por An N

3 de nov. de 2016

Good intro course for someone has no prior knowledge in Computer Vision. The entire course is about linear algebra practices. Professors provide lots of information, assignment projects are interesting.

por Salahuddin K

1 de abr. de 2018

Outstanding Course! I could always count on Prof.Jianbo to crunch some of the most complex and confusing parts of the course into a much easier understandable language.

por Rajeev K

24 de feb. de 2018

Course is nicely organized and helps even a novice without much in depth knowledge of image processing to understand the concepts

por Joe D

30 de nov. de 2016

Awesome material! I think this is the one course of the specialization that had the appropriate amount of work for the timeline.

por Srikanth V

17 de oct. de 2019

It is hard course, thoroughly enjoyed it. Lessons on how to effectively use vanishing points was very useful.

por 李晨曦

29 de jul. de 2017

Great lectures! I felt a little confused at the beginning , but everything makes sense by the end of class.

por Hamid M

2 de mar. de 2019

One of the most usefful courses I have taken by the coursera. Thank you for useful materail covered here.

por Abdelrhman H N

13 de may. de 2016

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

por Liang L

26 de dic. de 2018

The professors have very detailed description, and the programming assignments are valuable.

por Samuel D

12 de may. de 2016

Very good. Teachers worked hard. Practical and quite comprehensive for such short term.

por Lokesh B

27 de may. de 2018

This was by far the best course. Very difficult and complex. But it is worth studying

por Chinthaka A

24 de may. de 2019

Great course, I been able to develop new skills and knowledge. Highly Recommended.

por Abhishek G

20 de mar. de 2017

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

por Bernardo M R J

13 de ago. de 2016

Excellent course, very nice field of research with a lot of space for innovation.

por Shakti D S

27 de abr. de 2016

So many interesting concepts and theories, packed in a 4 week course.

Excellent.

por pavana a S

11 de ene. de 2019

Great course!. There is a lot of information. It should be a 6 week course!

por Sunaada H M N

3 de dic. de 2019

The assignments were challenging and the course videos were really good

por Dilshan M

1 de feb. de 2020

Great in-depth course into the fundamentals of perception in robotics.

por Wong H

20 de oct. de 2016

Good course, lecturers do their best to give u an informative course