Chevron Left
Retour à Robotics: Estimation and Learning

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

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


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.


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 :

101 - 109 sur 109 Avis pour Robotics: Estimation and Learning

par karthik r

31 oct. 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.

par Wilmer A R

9 juin 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

par Barak R

22 janv. 2021

the assignments in this course are impossible, full of errors and poorly explained.

this is a really interesting topic and most lectures are shallow and unrelated to the assignments.

errors and unexplained parts of the assignment wasted ALOT of my time for no reason

par Shaun L

11 avr. 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.

par Nick L

4 sept. 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.

par Rafael C

18 juin 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.

par Daniel C

25 nov. 2017

Lecture videos are extremely short and often not useful for the assignment. Also, the assignments are poorly written. Week 4 is the worst. I had to finish this course to unlock the last capstone project.

par Joaquin R

22 sept. 2018

Lack of detailed content, assigments WAY too difficult if you just take into account what was explained.

par Wang M

8 juin 2016

The assignment is meaningless. lack of instructions.