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Avis et commentaires pour d'étudiants pour Robotics: Perception par Université de Pennsylvanie

4.4
étoiles
509 évaluations
131 avis

À propos du cours

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....

Meilleurs avis

SK

Apr 01, 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

Jan 01, 2019

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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76 - 100 sur 127 Avis pour Robotics: Perception

par Liang M

Apr 17, 2017

A very good course in general. The materials and assignments are practical and the explanation of the instructors are clear. You are expect to gain a general knowledge about computer vision, camera calibration, and the usage of linear algebra in computer vision.

One thing that could be improved is that there is a big jump from week 2 to week 3 and also from week 3 to week 4. It's like a sophomore course at week 1 and week 2 and suddenly it jumps to a senior course in week 3 and a graduate course in week 4. It might be better to provide some supplementary materials in between.

par Fernando C

May 17, 2016

This course has a lot of interesting material regarding perception using cameras. The lectures focus on a wide range of topics, from the basics until camera pose estimation, epipolar geometry, optical flow and 3D motion. The explanations are very clear, and the Jacobian explanation using colors is excellent.

Negative points: sometimes the lectures are long, and the concepts are a little bit mixed.

par Qirui Z

Jun 06, 2019

Still some errors in the homework PDF (The codes are all working though). And the curriculum seems a little bit redundant. Also hope there will be more emphasis on emerging applications like visual odometry and SLAM, in stead of spending too much time on the ancient geometry (It's not expected to always have a checkerboard in your image? :-) ).

par Matthew P

May 03, 2018

The course was very detailed but perhaps a little too densely packed for a 4 week course. The instructors covered a very wide breadth of material in a very short time. I believe the instruction for the final assignment could be improved, but overall a good class introducing many important concepts in robotics and vision systems.

par Shaun K

Apr 04, 2017

Loved the lecture and materials. However, the course need more ACTIVE teaching staff and mentors. I had several questions regarding the materials but could not get any help from start to the end. It was the only specialization course that I had to move on without complete understanding of the materials.

par Lucila P

Nov 04, 2016

The course has a good structure. It covers interesting themas. The assignments are easy to understand. It takes more effort than 3 or 5 hours/week, the nomenclatur could be improved to be consistent. A couple of more examples would improve learning. The four week was hard ;)

par Lokesh

May 08, 2019

The course content is exceptionally well and material is well designed. Since most of the concepts are in-depth more support will be required in discussion forums. I feel the response from mentors is slow and have to wait days for their reply to clarify the doubts.

par hiback

Dec 19, 2018

The lecture is pretty good, learned a lot from it.But there are some bugs in assignment's pdf. Fortunately, our community forum pointed out these errors. Hoping they could fix it for better understanding.

par Adi S

Nov 09, 2019

The content is quite useful but the teaching can be improved upon through shorter videos and more animations instead of hand gestures (or static images) to explain mathematical derivations.

par SHAO G

Jun 17, 2017

The content is not very easy to understand because the lecture speaks very fast and the document is not very sufficient. But in all, the content is good, help me with my research.

par Liyun L

Feb 27, 2017

The 4th week content is hard to follow than the previous three. It would be better if more detailed math and examples are provided in the 4th week.

par Shengkai Z

Oct 26, 2018

Subtitles are generated by machines I think. Very many subtitles are wrong. It is very unfriendly to non-English speaking users.

par Jayant S

Jan 06, 2018

Extremely fast-paced course that gives a great overview of Perception but leaves a lot of things unexplained or without proofs.

par Ruslan A

Aug 21, 2017

Very interesting and useful course. Professors give a lot of information. However, some explanations are not very clear.

par Tim O

Dec 10, 2016

Lots of good content, good explanations, and good pictures to explain things. I enjoyed the assignments too

par Mohammad H

Jul 10, 2019

very useful course. However it needs some supplementary materials in math. also more solved examples.

par Iftach

Nov 06, 2016

very informative. the course is very demanding, due to very long lectures it is hard to stay in pace.

par Jesus F

Oct 20, 2016

Good course, but assignmets are too long, difficult and with no much help. Workload is overpassed

par Xiaotao G

Dec 16, 2018

It is hard compared to previous courses and need more time on it. But quite helpful!

par Mike Z

Oct 10, 2018

Really good topic but the material can be improved a lot more.

And it's free !

par Shubham W

Aug 13, 2017

Excellent course!! Especially Bundle Adjustment was covered in good details.

par Ricardo A R

Feb 14, 2019

Need more videos for final weeks, hard to follow last week of the course

par Daniel C

Dec 23, 2018

To put it simply: Shi's content is good and Danniilidis' content is bad.

par Aman B

Jan 29, 2019

It was interesting, but damn the lectures are never ending.

par yanghui

Oct 27, 2017

a bit difficult to understand, anyway,finally passed!