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Robotics: Estimation and Learning(으)로 돌아가기

펜실베이니아 대학교의 Robotics: Estimation and Learning 학습자 리뷰 및 피드백

382개의 평가
87개의 리뷰

강좌 소개

How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping....

최상위 리뷰


Feb 16, 2017

The material is clearly presented. The Matlab exercises complement and reinforce the subject, the level of difficulty is well balanced, thanks for this great course.


Jun 20, 2016

This is course is really helpful for beginners to understand how probability is useful in Robotics.Assignments are bit tough but worth the time .

필터링 기준:

Robotics: Estimation and Learning의 82개 리뷰 중 76~82

교육 기관: Rafael C

Jun 18, 2016

You need to have deep knowledge in matlab to get pass the assignments. I have spent more time figuring out how the simulations are implemented that really learning about the target algorithm to implement.

교육 기관: Wilmer A R

Jun 09, 2016

A lot of things to improve, specially thr learning courve is from 1 to 100 and a lot of pre knowledge need, your future public is the hobby robotics people who want to expand their knowledge, a litlle more weeks maybe two can increase the likes for the course. Check this one Control of Mobile Robots you can get an example of a good learning curve

교육 기관: Eduardo K d S

Oct 26, 2016

I wouldn't recommend this course to my worst enemy. There is 0 commitment from the TA and mentor staff. After 4 weeks of course, not a single reply from any of them in the forums.

To make matters worse, the material is very superficial and lacking, the biggest proof of that is that each module is composed of about 4 videos of 5 minutes each! How can you learn anything in 5 minutes? The topics are so complex, there is simply no way to convey their message in just about 5 minutes. I had to search a lot outside of this course to grasp something of the topics covered. Actually, I found way better explained videos on youtube for free.

The assignments of this course are poorly developed and don't reflect what is discussed in the videos well. I repeat myself, the study material was very lacking and consequently not enough for the assignments themselves. I had to spend days coding, debugging and reverse engineering the assignment files to finally be able to pass because they were wrong! They were incomplete and had wrong information. This is not a reverse engineering course... I shouldn't need to do that. Anyway, I did it because there was also no help from any TA to guide me in the right direction.

Long story short, you are way better off checking the syllabus of this course and checking videos on youtube to learn about them, you'll learn way more than with this money grabber course.

교육 기관: karthik r

Oct 31, 2017

Although the course is structured properly, the lectures are horrible, explanation for kalman filter lasts couple of minutes,while in universities the topic is studied and implemented as thesis over 6 months, week 4 also throws very poor insight on particle filter, week1 and week3 were better explained. I've learnt more from youtube , The lecturers should see how Andrew Ng teaches his courses, he works through the algorithms step by step. I had to painfully finish this course to unlock the capstone project. I do not recommend this course if you are new to robotics.

교육 기관: ShuYu W

Jun 08, 2016

The assignment is meaningless. lack of instructions.

교육 기관: Nick L

Sep 04, 2016

Barely any contents in the course. Only a few minutes of lectures, no quizzes and poorly constructed assignments that waste a lot of time. Weeks 2 and 4 have the worst material I've seen in all the courses I've taken until today.

교육 기관: Shaun L

Apr 12, 2018

The professor left all the teaching to his Phd students. The material was not straight forward, and possibly made even more difficult with the lackluster slides and presentation. A pdf explaining the theories would be more helpful.