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Voltar para Robotics: Perception

Comentários e feedback de alunos de Robotics: Perception da instituição Universidade da Pensilvânia

4.4
estrelas
585 classificações
157 avaliações

Sobre o curso

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....

Melhores avaliações

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.

SM
4 de Jan de 2021

Great course for those who wants to understand how classical SLAM systems work. I think it would be a bit more practical if the assignments were made in python.

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101 — 125 de 154 Avaliações para o Robotics: Perception

por Jayant S

6 de Jan de 2018

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

por NICHOLAS P

25 de Nov de 2020

Interesting material, the last programming assignment was very challenging. Lots of topics covered, a good introduction.

por Ruslan A

21 de Ago de 2017

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

por Tim O

10 de Dez de 2016

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

por Mohammad H

10 de Jul de 2019

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

por Iftach F

6 de Nov de 2016

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

por Jesus F

20 de Out de 2016

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

por Xiaotao G

16 de Dez de 2018

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

por Rahul D

29 de Mar de 2020

I was expecting Some implementation of the SFM pipeline from OpenCV or OpenMVG.

por Mike Z

10 de Out de 2018

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

And it's free !

por Shubham W

13 de Ago de 2017

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

por Ricardo A R

14 de Fev de 2019

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

por Daniel C

23 de Dez de 2018

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

por Aman B

29 de Jan de 2019

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

por yanghui

27 de Out de 2017

a bit difficult to understand, anyway,finally passed!

por Ákos G

13 de Set de 2020

Good course, but the video subtitles are garbage.

por xiao z

3 de Mai de 2020

need specific feed backs for those quizzes!!!

por li q

10 de Ago de 2016

The lecture notes should be better organized.

por Luming

22 de Set de 2020

a little difficult for me,but learn a lot!

por Hussain M A

1 de Out de 2019

Hard course but lots of good insight.

por Martin X

23 de Out de 2016

The courses are good and helpful.

por Ali M H

16 de Out de 2018

Thank you Professors !

por Jeffrey

18 de Fev de 2017

Unclear explaination

por Fredo P C

3 de Fev de 2019

Great Course!

por Daniel S

20 de Mai de 2017

This course could use some help. It's a very interesting and important topic and is also difficult, but it could be explained better and the tie in between the lecture videos, quizzes and homework assignments could also be better. Some of the quiz questions are not answerable from reviewing the lecture notes and require outside knowledge of linear algebra and rotation mathematics. The assignments should also be better defined and set up so that there is incremental feedback available for the intermediate steps. For example, the last week's assignment has 5 steps, each of which requires a Matlab function to be written. In many online courses, there are "correct" intermediate results given so that each step can be verified before proceeding to the next step. In this assignment, there is not much feedback until you get to the third or fourth step and even then it's not the best. I had an error in one of the functions, but the problem feedback (photo comparisons) showed it as being OK until I submitted it for grading. It's important, since there's no instructor feedback , to provide some means of checking if you're doing things correctly.Some of the terminology used would be more clear if it was standardized; sometimes coordinates are x and y, sometimes u and v, there's also u1, u2, u3 and things like X = [x,y,z,w] and x = [u,v,w]. Its often quite difficult to know what's being referred to it's called x. I did learn a lot from this course, but it could have been a lot easier.