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Volver a Robotics: Perception

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

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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


31 de ene. de 2021

This course was truly amazing. It was challenging and I learned a lot of cool stuff. It would have been better if more animations were included in explaining complex concepts and equations.


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.

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151 - 174 de 174 revisiones para Robotics: Perception

por Timothy M

9 de jul. de 2017

some interesting material. The Slides for week 2 and 4 are terrible, too condensed with very little explanation on difficult topics. The Homeworks are pretty interesting, the assignments for week 3 and 4 complement eachother very well. the week 2 Kalman filter assignment didn't seem to work. I submitted something in frustration and was very surprised that it was accepted.

por Volodymyr K

15 de jun. de 2016

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.

por 王天东

2 de jul. de 2019

It's a nice introduction, but a lot of details are not well explained. A lot of typos in homework, epecially in Equations. This is very bad for UX. And few of mentors are maintaining this course. If you ask questions in forum, you can not get repsonse quickly. I suggest that mentors should spend some time to correct typos and upload some supplement materials.

por Pranav K

15 de ago. de 2020

The content in the course and the expanse of knowledge covered is excellent. I would suggest that course be more organized in terms of terminology and usage of symbols. It does take time, but using different notations while explaining the same concepts causes confusion, at least during the learning phase. Overall a great course.

por Ray.Gong

3 de may. de 2018

The content is undoubtedly valuable and instructive, but for some topics in week 3 & 4 the content isn't organized in a good order. Most importantly, no one answers my questions in the forum, and I felt helpless when the lecturer and slides fail to clearly explain some complex concepts.

por Rahul H

28 de dic. de 2021

The course had a lot of useful content and a lot of information. Although the presentation was not that good. The slides could have used more of text, there were only formula and images. Week 4 exercise could have been given a little more clearly in the Exercise sheet.

por Martin Z

6 de mar. de 2019

There were a lot of error in the materials even after all those years. Also the instructor's English is hard to understand sometimes. In addition to that they do a lot of waving around with their hands instead of marking things directly in the pictures.

por Fabio B

4 de ago. de 2017

The course is excellent is computer vision! The only problem it is not didactic at all, so if you don't are familiar with this content it will be very hard (even impossible) to follow.

por Casey B

29 de ago. de 2018

Lectures sometimes scattered and hard to follow. More advanced visuals would be helpful for such a visual subject vs watching lecturers wave hands and point at things.

por Adarsh S

29 de abr. de 2020

Topics are good and comprehensive, but videos are long and difficult to follow, with a lot of additional research necessary to truly understand the concepts.

por Francisco C M M

6 de may. de 2020

The content was great and not so easy, you need good math-linear algebra background, bur for some reason I didn't enjoy the course :/

por Andrey S

13 de abr. de 2017

Too much theory and projects didn't related with real life problems.

por Christos P

22 de dic. de 2020

Visual Perception (Computer Vision) < Perception

Too math oriented

por Wahyu G

15 de ago. de 2018

Very though and little help in the discussion forum

por Alejandro A V

3 de may. de 2016

The videos are so long in time and not very clear.

por Yiğit U

29 de abr. de 2016

Lessons and videos are very long for one week.

por Deepak P

10 de abr. de 2019

Not at all formulated for bachelors

por Chris F

8 de may. de 2016

Professors very hard to understand, and videos don't have the best editing.

Also extremely math heavy, lectures being just math formulas, without a lot of real life applicability (ex. the assignments where you have to project a logo, or cube, when the program gives you the location corners in a file, which will NEVER happen when you use your camera; finding that position is a pre-requisite of the entire program)

por David L

19 de may. de 2016

This course should have been very good. Lots of detail. But the material is not presented very clearly. The Assignments are also not setup so that it is easy to fix your work. It either passes, or you get minimal feedback.

por Omar E

21 de jun. de 2022

Content feels all over the place, the instructors explaining is lacking, generally an uninteresting course for the topic matter

por Mohammed A 2

22 de jun. de 2022

Very bad illustrations, the instructors are explaining using thier hands in the air, how can I know which line is he referring to while he is showing with his hands in air ?

Bad visual aids

Bad preparation, most of the time the instructors appear that they are just reading a script, not explaining

fun fact; that in one of the videos the instructor was confused and then said "I will repeate again" and then continue reading the script

por Ashar J

9 de nov. de 2022

The course is poorly managed, no proper explanation is given for a lot of mathematical methods used in the course, and the content is challenging to follow due to less amount of descriptions and breaks in the steps hence I am forced to watch the video again to understand the concept making sure that I don't miss the difficult to understand accent. The slides are not helpful.

por HG L

6 de may. de 2022

Worst course ever had on Coursera. Bad illustrations and cumbersome body languages just make the explanation of the concepts more confusing. Maybe the Andrew Ng's machine learning and deep learning specialization are just too good, so that it makes me feel this course is unacceptably bad.

por Matthias K

5 de sep. de 2020

I need help