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.
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.
創建者 Guining O•
Some more help or examples should have been provided for the programming exercises, especially the last one
創建者 Qiu Q•
This course is very useful and interesting, but the materials of week 2 & 4 is enough for their quizs.
Poor structuring of assignments. Unclear objectives and wrong input data.
Course Content was good.
創建者 Ramya J•
The assignments were very confusing, you should explain them a bit more in the lecture videos.
創建者 ADITYA N•
Wish had a proper explanation and more detailed derivations or understanding of basics
創建者 Bhavya G G•
Some lectures were clearly explained, some lectures required prerequisite knowledge
Who teaching us is a student, and the assignment is not in detail as other class
創建者 Alex F•
Good programming exercises but very bad lectures
創建者 Damoun L•
very minimal presentation of many concepts!
創建者 juha n•
Assignments need some serious revising.
創建者 Dhagash D•
Not deeply explained not for beginneer.
Too hard for beginner for last 3 week
創建者 Troy W•
Really too short.
創建者 Fredo C•
創建者 Raunak H•
創建者 Enrico A•
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.
創建者 Behrooz S•
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.
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.
創建者 Nick P•
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.
創建者 Juan Á F M•
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.
創建者 Timothy O•
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.
創建者 Yiming Z•
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.
創建者 Alejandro A V•
It is not very clear. The assignments have several problems with the given code. There are many things to improve in the next sessions.
創建者 Gaurang G•
Week 2 kalman filter assignment not clear;
Course can be made more clear like Aerial Robotics.
創建者 Nico W•
What's there is ok, but there is only a few minutes of lecture material each week.