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Robotics: Computational Motion Planning(으)로 돌아가기

펜실베이니아 대학교의 Robotics: Computational Motion Planning 학습자 리뷰 및 피드백

4.2
766개의 평가
196개의 리뷰

강좌 소개

Robotic systems typically include three components: a mechanism which is capable of exerting forces and torques on the environment, a perception system for sensing the world and a decision and control system which modulates the robot's behavior to achieve the desired ends. In this course we will consider the problem of how a robot decides what to do to achieve its goals. This problem is often referred to as Motion Planning and it has been formulated in various ways to model different situations. You will learn some of the most common approaches to addressing this problem including graph-based methods, randomized planners and artificial potential fields. Throughout the course, we will discuss the aspects of the problem that make planning challenging....

최상위 리뷰

FC

Nov 28, 2018

The course was challenging, but fulfilling. Thank you Coursera and University of Pennsylvania for giving this wonderful experience and opportunity that I might not experience in our local community!

AD

Jul 03, 2018

The topic was very interesting, and the assignments weren't overly complicated. Overall, the lesson was fun and informative , despite the bugs in the learning tool(especially, the last assignment.)

필터링 기준:

Robotics: Computational Motion Planning의 190개 리뷰 중 176~190

교육 기관: K0r01

Jan 11, 2018

robustness of assignment auto-grader completely ruined the experience of this course.

교육 기관: Raymond N H A

Mar 30, 2016

Lack of support from course teaching staff in answering student's questions.

교육 기관: Jason D

Feb 29, 2016

The course is very bad and feels thrown together at the last minute. Learning A* and Dijkstra's algorithm is great however the assignments require you to learn not just the little details but to "discovery" techniques not even mentioned in the course material. In addition, you must have strong matlab programming skills and be familiar with much matlab functionality in order to debug some of the assignments. You must have more knowledge concerning matlab than any of the course material or pointers provides. Meaning that beginners will NOT pass this course. The automatic grader provides no feedback at all except pass or fail. This is unfortunate as it can look like your code is working correctly but, the grader is using some edge cases to grade the code but will not include any information indicating what to look for. This is really atrocious. Although the TA's do occasionally provide answers to questions. The total amount of time TA's spend answering questions is just really poor. Don't expect even well asked questions to be answered at all. In addition, the coded template quality upon which your own code depends is horrible and thrown together. You will spend way too much time analyzing it for clues as to what went wrong. Sadly, enough all of these issues have caught up with me and I was unable to pass assignment 2 part 2. Even, though everything looks like it works and achieves the desired goal and even works with all of my own test cases. The grader is merciless. Perhaps, in the feature more time can be devoted to make this course better and I can spend more time learning how the algorithms and maths work rather than matlab and the automatic grader. At this time I don't feel like my money was well spent on these courses. I don't think I would like to risk another 50 dollars learning matlab and debugging the automatic grader on any of the other courses in this specialization. That is very disappointing as I really am passionate about learning robotics and looked forward to the other courses as well.

교육 기관: Nico W

Feb 22, 2016

This is part 2 in the robotics specialization. The course content is way too short and basic for the price. There are about 77 minutes of lecture in total, i.e. less than 20 minutes per week. The first week covers BFS, Dijkstra, and A*, something part of most undergrad programs. The rest of the material is ok but very basic. The programming assignments are "implement Dijkstra" in week 1, "implement Dijkstra on a Torus" (and "do triangles intersect?") in week 2, a very simple for loop in week 3, and "implement gradient descent" in week 4. I could complete the course by looking at it on-and-off over one weekend.

The material that is presented is presented well, but there's not enough of it.

For reference, part 1 of the robotics specialization had over twice as much lecture content (by time) and then lots of supplementary material in addition to that, quizzes that required some thinking, and more relevant and at least slightly harder programming assignments.

교육 기관: James L

Mar 20, 2016

This is the second of the series, and I had high hopes for this one after the first one was a disappointment.

While the material was on the sparse side, the level of the course was more as advertised. The Matlab assignments were not too difficult, but were relevant enough to the material to be acceptable. Some of the assignment simulations/animations were not working, but I was able to submit the results and get full credit. I was ready to give 2 or 3 stars in this review.

Unfortunately, on the last assignment, the sample code and scripts was buggy (even towards the end of the course after it had been pointed out to the staff), and inconsistently written.

The final project submit script would not work and it was a trial and error troubleshooting to understand why. Some on the discussion boards were able to submit, but other couldn't. Although my assignment would run as I understand the project should, I could not even submit it. Judging from the discussion boards, I'm not the only one with this problem.

Again, the University of Pennsylvania has missed the mark with this class and the robotics series. It is regretful that I must again leave a one star review.

I realize this is the first time this course was offered, so there are some issues that need to be worked out. I suggest for the remainder of the classes in the series, the creators should do a pilot run first before releasing to Coursera.

교육 기관: Aditya M D

Oct 25, 2016

Could have been awesome course if it discussed some detailed approaches. Only 3 panning approaches discussed in 4 weeks, thus disappointing.

교육 기관: Brook

Oct 23, 2017

However enthusiastic or clear CJ was in the lecture videos, the subject matter was not given adequate coverage. The entire set of lecture videos is about 1h 30min; other courses in the same specialization have about the same content in a one week session. Materials discussed such as configuration space should have been given in depth treatment. On the other hand, there was no mention of sampling based motion planning, MDP etc. In the current state that this course is in, it should be integrated with the Estimation and Learning course.

교육 기관: Ihor Y

Mar 14, 2016

I believe Penn can do better

교육 기관: Jiaming S

Mar 14, 2016

Sorry to say that this is not a well prepared course. The course video provided is quite short, the quiz is rather than nothing and the programming assignments are buggy. I don't feel that I learned a lot from this course.

UPenn has let me down twice. Hope the 3rd one will be better.

교육 기관: Ahmed A E

Mar 06, 2016

The course is so weak. No enough illustration for the content of the course. It's too short and not prepared very well.

교육 기관: Iwan P

Mar 15, 2016

The topic is interesting and the lectures itself were good. The explanations of the algorithms and concepts was clear and easy to understand. However, the amount of material covered is very little. I think there should either be more concepts thought or they should be covered in more depth.

Quizzes: The quizzes were very weak. They didn't really tell you weather you understood the concept or not. If one of the answers was wrong there was no information which one it was. So you have no idea which lecture you should watch again.

Assignments: The assignments were very bad prepared. In some assignments there were bugs in the provided code, we weren't supposed to edit. The assignments itself are rather easy and can be completed quite quickly, if there wasn't the grader. From the grading you got no information what was wrong or which tests passed or failed. Most of the time it wasn't the case that the algorithm failed, instead the output was not as expected by the grader, although it was as described in the assignment. But you never knew. This part has to be improved a lot.

Overall I have to say that I expected much more from University of Pennsylvania, especially after taking the first part of the Specialization which was of good quality.

교육 기관: Piotr G

Apr 01, 2016

This course need a serious rework.

For the moment I finished it biggest problem was very unclear grading of programming assignments and lack of learning materials.

교육 기관: Oscar d l H I

Feb 14, 2017

All the assignments are so unclear and you´ve to lose so much time trying to understand the goal of the problem.

교육 기관: Qi L

Feb 20, 2016

The assignment code is ambiguous and the assignment is not clear! The lecture is not much helpful than I thought it would be. Overall, I would not recommend this course if you don't need the certificate.

교육 기관: Emre T

Sep 03, 2017

I have completed 4 courses with this one , and I can say that this is the far worst. Course material is not enough. Assignments are not prepared well and instructions are not adequate. I realize that one must show a fair amount of effort to learn a subject, however, in this course it is almost like TA's are trying to make it difficult us to learn. You must enrich the course material that one should be able to go deep in subject and make the assignments clearer .