Chevron Left
Retour à Robotics: Estimation and Learning

Avis et commentaires pour d'étudiants pour Robotics: Estimation and Learning par Université de Pennsylvanie

4.3
étoiles
490 évaluations

À propos du cours

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....

Meilleurs avis

VG

15 févr. 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.

DA

5 févr. 2021

This course was interesting but I think the video material was too shallow and not detailed enough. The assignment for Week 4 was extremely challenging!

Filtrer par :

76 - 100 sur 109 Avis pour Robotics: Estimation and Learning

par Guining O

18 févr. 2019

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

par Qiu Q

12 sept. 2016

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

par Saif

20 juin 2016

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

Course Content was good.

par Ramya J

14 janv. 2022

The assignments were very confusing, you should explain them a bit more in the lecture videos.

par ADITYA N

3 mai 2020

Wish had a proper explanation and more detailed derivations or understanding of basics

par Bhavya G G

19 avr. 2021

Some lectures were clearly explained, some lectures required prerequisite knowledge

par 陈旭展

17 mai 2016

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

par Alex F

4 févr. 2020

Good programming exercises but very bad lectures

par Damoun L

18 févr. 2017

very minimal presentation of many concepts!

par juha n

15 juil. 2018

Assignments need some serious revising.

par Dhagash D

11 déc. 2016

Not deeply explained not for beginneer.

par Luming

30 oct. 2021

Too hard for beginner for last 3 week

par Troy W

16 mai 2016

Really too short.

par Fredo C

17 mars 2019

Difficult course

par Raunak H

18 déc. 2017

Meh

par Enrico A

29 juil. 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.

par Behrooz S

9 juin 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.

par 李晨曦

29 juil. 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.

par Nick P

11 déc. 2020

The programming assignments are interesting, however they are not well documented nor are they well constructed. Lecture videos are just a few minutes each week, and do a very poor job of setting up assignments or explaining the material. You will spend most of your time on the forums, and doing your own research.

par Juan Á F M

4 août 2018

All in all, it's a very interesting, absolutely necessary topic for robotics. But everything is treated here without theory tests, detailed examples and the like, so learning is only tested with programming tasks. The student must work a lot with MATLAB to come up with crafty solutions for week practices.

par Timothy O

10 déc. 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.

par Yiming Z

14 oct. 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.

par Alejandro A V

8 juin 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.

par Gaurang G

6 mai 2017

Week 2 kalman filter assignment not clear;

Course can be made more clear like Aerial Robotics.

par Nico W

5 févr. 2017

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