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Opiniones y comentarios de aprendices correspondientes a Robotics: Estimation and Learning por parte de Universidad de Pensilvania

4.3
400 calificaciones
91 revisiones

Acerca del Curso

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....

Principales revisiones

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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51 - 75 de 85 revisiones para Robotics: Estimation and Learning

por Fredo P C

Mar 17, 2019

Difficult course

por Guining P

Feb 18, 2019

Some more help or examples should have been provided for the programming exercises, especially the last one

por juha n

Jul 15, 2018

Assignments need some serious revising.

por 陈旭展

May 17, 2016

Who teaching us is a student, and the assignment is not in detail as other class

por Fabio B

Aug 17, 2017

Not an easy course, very difficult for beginner students. I considered myself an advanced student (have a PhD in the field) and even I found it difficult sometimes. In any case it is an excellent course.

por Rishabh B

Jun 25, 2016

Course contents are very short and to the point. I thought weeks on Gaussian Model Learning and Robot Mapping were neat. But the other two weeks on Kalman filter and Particle Localization were little disappointing. They could have discussed both these topics properly by investing more time. Couple of Assignments are tough and there will be very little help to complete it but nevertheless it will keep you interested in the course.

por Matthew P

May 14, 2018

This course covers some very important techniques in modern robotics including Kalman filters, mapping, and Particle filters. However, the way that these topics are presented in this course is not very clear. The later lectures especially lack the necessary content to provide a clear understanding of advanced topics. The final assignment in particular is very poorly documented and the included instructions are a bit misleading. In addition to that, the forums seem to have been abandoned by the course instructors and are full of unanswered questions from struggling students, some of them more than a year old. This course needs some serious attention and revision. Definitely the lowest quality course of this series.

por Damoun L

Feb 18, 2017

very minimal presentation of many concepts!

por Raunak H

Dec 18, 2017

Meh

por Saurabh M

Jul 06, 2018

The course structure is nice. However there is little explanation for the programming assignments, especially the last one (week 4). For other weeks I got good help from the forums however the forums do not have much threads and many are unanswered. It would be great if more reading material can be added for that week.

por Dhagash D

Dec 11, 2016

Not deeply explained not for beginneer.

por Troy W

May 16, 2016

Really too short.

por Qiu Q

Sep 12, 2016

This course is very useful and interesting, but the materials of week 2 & 4 is enough for their quizs.

por Saif

Jun 20, 2016

Poor structuring of assignments. Unclear objectives and wrong input data.

Course Content was good.

por Iftach

Oct 29, 2016

need more lectures. there are complicated topics with weak background for the students.

except that it is a great course. thanks..

por Yuanxuan W

Aug 15, 2018

Good course schedule, but videos in week 2 and week 4 really need some rework. There are errors in slides and videos are too vague to be helpful, I have to look for external materials to understand the topics (Kalman Filter and Particle Filter).

por Gasser N

Sep 12, 2019

this course is great but i felt that the staff are assuming that we know a lot about probability which is not correct , week 4 is very poor and it's very hard to understand it ,hope they can fix this.

por Yiming Z

Oct 15, 2017

Poor explanations in the lectures especially for particle filter.

It doesn't go deep into why and how the method was developed in a theoretical way.

por Alejandro A V

Jun 08, 2016

It is not very clear. The assignments have several problems with the given code. There are many things to improve in the next sessions.

por 李晨曦

Jul 30, 2017

The lectures does not provide enough information and dig into the underlying principles. Lectures that are supposed to be half an hour are condensed into several minutes. Of all the courses in this series, I rely on external resources and forums the most to finish this one. I honestly think the teaching staff could do a better job.

por Behrooz S

Jun 10, 2016

Very important materials are explained super briefly. I would only suggest it for getting familiar with the estimation "keywords and terminologies" or for someone who wants to brush up his/her prior knowledge in estimation. The total session time for all 4 weeks together is only a few hours and the homeworks do not cover the session topics.

por Nico W

Feb 05, 2017

What's there is ok, but there is only a few minutes of lecture material each week.

por Enrico A

Jul 29, 2017

The material covered is very interesting. However, I am a bit disappointed by the lecture format and the assignment preparation. It is good to have concise lectures that stick to the core of the subject. However, in this case, they were not very clear. Additionally, the assignments tend to be cover different material from the lectures. Besides, they are not well explained and it is difficult to understand what is required. You basically end up doing a lot of trial and error. Luckily, the blog contains very useful posts from other frustrated users.

por Gaurang G

May 06, 2017

Week 2 kalman filter assignment not clear;

Course can be made more clear like Aerial Robotics.

por Tim O

Dec 10, 2016

When I took, assignments 2 and 4 were broken and there were no mentors to help students. However, I am now told they will be fixing the course. I give 2 stars becuase the concepts of the assignments is good, but the course needs more attention.