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Learner Reviews & Feedback for Robotics: Perception by University of Pennsylvania

4.3
stars
642 ratings

About the Course

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....

Top reviews

DA

Jan 31, 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.

SK

Mar 31, 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 - 175 of 176 Reviews for Robotics: Perception

By Carlos R

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May 14, 2016

I dont like how this course was presented. The professors are good but the way how they present the course is extremely inefficient. I mean, because the instructor only speaks moving hands from one side to other, it was very difficult to visualize what and where the instructor was referencing to. Eg. a figure with 3 formulas and many variables there was no way to know in what alpha variable in formulas the instructor was talking about, once all formulas had the alpha variable. Also, when trying to describe a 3D environment only moving hands, its quite impossible to determine what and where the instructor is. One suggestion to try to minimize this problem would be try to use a lase pointer or a stick or a pen or something similar to help the student to now where the instructor exactly is. One example of good presentation is the course of ML from Andrew Ng where he writes all the things while speaking which facilitates the student to follow the sequence. Hope this can help.

By James T

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Jan 1, 2024

(I have left the same comments for each course in the specialization.) There is a lot of good content, but the program is essentially orphaned. The instructors do not engage to any significant degree, and the level of learner engagement in the forums is minimal. If you have difficulties with the assignments, you may find yourself combing through years-old posts, hoping that someone in the past dealt with the same issue that you are having and posted some useful information. The sequence of courses is nonetheless a useful resource for self-study, but expect some frustration in completing the programming assignments, especially in the later courses, since you are unlikely to receive any direct support.

By Timothy M

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Jul 9, 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.

By Vol K

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Jun 15, 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.

By td w

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Jul 2, 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.

By Pranav K

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Aug 15, 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.

By Ray.Gong

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May 3, 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.

By Rahul H

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Dec 28, 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.

By Martin Z

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Mar 6, 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.

By Fabio B

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Aug 4, 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.

By Casey B

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Aug 29, 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.

By Adarsh S

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Apr 29, 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.

By Francisco C M M

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May 6, 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 :/

By Andrey S

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Apr 13, 2017

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

By Christos P

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Dec 22, 2020

Visual Perception (Computer Vision) < Perception

Too math oriented

By Wahyu G

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Aug 15, 2018

Very though and little help in the discussion forum

By Alejandro A V

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May 3, 2016

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

By YiÄŸit U

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Apr 29, 2016

Lessons and videos are very long for one week.

By Deepak P

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Apr 10, 2019

Not at all formulated for bachelors

By Chris F

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May 8, 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)

By David L

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May 19, 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.

By Omar E

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Jun 21, 2022

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

By Mohammed A

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Jun 22, 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

By Ashar J

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Nov 9, 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.

By HG L

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May 6, 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.