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学生对 宾夕法尼亚大学 提供的 Robotics: Estimation and Learning 的评价和反馈

4.3
411 个评分
94 条评论

课程概述

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....

热门审阅

SS

Apr 07, 2017

Leanring of mechanism and implementation of Kalman filter and particle filter from experiment is very interesting for me. And these method let me know more about map building in SLAM framework.

VG

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.

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1 - Robotics: Estimation and Learning 的 25 个评论(共 88 个)

创建者 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.

创建者 Tri W G

Mar 24, 2018

Pretty short course but it is really worth it if you want to learn about SLAM. Just like any other courses in this specialization, help in the forums is really minimum and the course is pretty though, so you have to spend more time to complete the course. Overall it is a great course, at least for me. Thank you for all lecturers.

创建者 Janzaib M

Apr 04, 2017

Here I learnt all the building blocks of Probabilistic Robotics and the significance of statistical methods etc to deal with the the non-linear world.

The course content is very concise and to the point. And, the knowledge transferred is well structured.

创建者 Louis B

Jun 30, 2019

This lecture is very useful from the perspective of approaching robotics for the first time. I recommend it!

There was a lot of effort to get back to the normal distribution I had studied before, but it was very good.

创建者 Shuang S

Apr 07, 2017

Leanring of mechanism and implementation of Kalman filter and particle filter from experiment is very interesting for me. And these method let me know more about map building in SLAM framework.

创建者 vincent g

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.

创建者 Niju M N

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 .

创建者 Abhilash V

Jun 25, 2016

A tough course with few hours of lecture material and some good programming assignments.You will be satisfied by those assignments however .

创建者 Adi S

Nov 23, 2019

Really good course. Engaging and relevant content. The assignments push you but test your fundamentals and you end up learning a lot.

创建者 Vu N M

Sep 19, 2018

This is a really comprehensive course which gave me a good knowledge about Gaussian Model and Kalman Filter ...

创建者 SHAO G

Dec 14, 2016

It's a great course. Although the assignment is little tough, you will gain a lot after completing it.

创建者 Shubham G

Mar 03, 2018

Very succinct lectures which provides necessary foundation to learn advanced localization algorithms.

创建者 李鹏飞

Aug 08, 2017

It's a really great course and I learn a lot of things which helps me get started with this subject!

创建者 KALVAPALLI S P K

Aug 29, 2019

week 2 and 4 needs more information. Yet great learning experience at affordable price.

创建者 Lieke V

Jun 13, 2016

Contents relevant, lectures well paced and clear and TA's very helpful and on it!

创建者 Mingrui Z

Mar 25, 2018

Good materials for beginners. Assignments are interesting and useful.

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创建者 Dilshan M

Feb 01, 2020

Excellent course in estimation and implementation of Kalman Filters.

创建者 Shounak D

May 23, 2018

good course ..expecting more follow up courses on this topic !

创建者 akshay s

Nov 02, 2016

Really nice course with a lot of good content.

创建者 Akhilesh K

Sep 06, 2017

Challenging but great course to learn.

创建者 Guillermo C

Aug 21, 2017

Challenging and very well delivered.

创建者 Jianxin L

Oct 13, 2017

It is a good course, like it.

创建者 Aryan A

Sep 21, 2018

Great course learnt a lot !!

创建者 Utku K

Oct 11, 2016

Very good and informative.

创建者 丘广俊

Feb 23, 2017

It make me to know more!