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Avis et commentaires pour l'étudiant pour Robotics: Estimation and Learning par Université de Pennsylvanie

4.2
384 notes
88 avis

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

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.

NN

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 .

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1 - 25 sur 82 Examens pour Robotics: Estimation and Learning

par Bálint - H F

Mar 20, 2019

Great ! Difficult !

par Aryan A

Sep 21, 2018

Great course learnt a lot !!

par 王維煜

Oct 16, 2016

好極了,有中文的字幕,非常輕鬆,謝謝!

par akshay s

Nov 02, 2016

Really nice course with a lot of good content.

par 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.

par SHAO G

Dec 14, 2016

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

par Jianxin L

Oct 13, 2017

It is a good course, like it.

par 周天宇

Oct 09, 2017

希望理论部分讲的再深入些!

par jiqirenzhifu

Aug 12, 2017

nice

par 爽 宋

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.

par 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.

par 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 .

par 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!

par Talha Y

Jun 12, 2016

veryyyyyyyyyyyyy good

par 丘广俊

Feb 23, 2017

It make me to know more!

par K0r01

Jan 19, 2018

robust material

par Shubham G

Mar 03, 2018

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

par Guillermo C

Aug 21, 2017

Challenging and very well delivered.

par Lieke V

Jun 13, 2016

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

par Abhishek G

Sep 11, 2016

Highly recommended!!

par 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 .

par Utku K

Oct 11, 2016

Very good and informative.

par Akhilesh K

Sep 06, 2017

Challenging but great course to learn.

par 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.

par Shounak D

May 23, 2018

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