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Вернуться к Robotics: Perception

Отзывы учащихся о курсе Robotics: Perception от партнера Пенсильванский университет

Оценки: 586
Рецензии: 158

О курсе

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....

Лучшие рецензии

31 мар. 2018 г.

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.

4 янв. 2021 г.

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 из 155 отзывов о курсе Robotics: Perception

автор: Jayant S

6 янв. 2018 г.

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


25 нояб. 2020 г.

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

автор: Ruslan A

21 авг. 2017 г.

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

автор: Tim O

10 дек. 2016 г.

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

автор: Mohammad H

10 июля 2019 г.

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

автор: Iftach F

6 нояб. 2016 г.

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

автор: Jesus F

20 окт. 2016 г.

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

автор: Xiaotao G

16 дек. 2018 г.

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

автор: Rahul D

29 мар. 2020 г.

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

автор: Mike Z

10 окт. 2018 г.

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

And it's free !

автор: Shubham W

13 авг. 2017 г.

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

автор: Jean K G R

24 янв. 2021 г.

In some activities, the theory wasn't enough to complete the assignments

автор: Ricardo A R

14 февр. 2019 г.

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

автор: Daniel C

23 дек. 2018 г.

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

автор: Aman B

29 янв. 2019 г.

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

автор: yanghui

27 окт. 2017 г.

a bit difficult to understand, anyway,finally passed!

автор: Ákos G

13 сент. 2020 г.

Good course, but the video subtitles are garbage.

автор: xiao z

3 мая 2020 г.

need specific feed backs for those quizzes!!!

автор: li q

10 авг. 2016 г.

The lecture notes should be better organized.

автор: Luming

22 сент. 2020 г.

a little difficult for me,but learn a lot!

автор: Hussain M A

1 окт. 2019 г.

Hard course but lots of good insight.

автор: Martin X

23 окт. 2016 г.

The courses are good and helpful.

автор: Ali M H

16 окт. 2018 г.

Thank you Professors !

автор: Jeffrey

18 февр. 2017 г.

Unclear explaination

автор: Fredo P C

3 февр. 2019 г.

Great Course!