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Robotics: Computational Motion Planning(으)로 돌아가기

펜실베이니아 대학교의 Robotics: Computational Motion Planning 학습자 리뷰 및 피드백

956개의 평가
243개의 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

2018년 11월 27일

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!

2018년 7월 2일

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 237개 리뷰 중 226~237

교육 기관: Iwan P

2016년 3월 15일

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: Nico W

2016년 2월 21일

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: B W

2017년 10월 22일

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: Emre T

2017년 9월 3일

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 .

교육 기관: Qi L

2016년 2월 20일

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: Piotr G

2016년 4월 1일

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: Erick A M D

2020년 11월 4일

The course is very basic. The lectures last less than 1 hour each week.

In the other hand, the Assignments have some errors that make you waste a lot of time.

교육 기관: Aditya M D

2016년 10월 25일

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

교육 기관: Ahmed A E

2016년 3월 6일

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: Oscar d l H I

2017년 2월 14일

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

교육 기관: K0r01

2018년 1월 11일

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

교육 기관: Ihor Y

2016년 3월 14일

I believe Penn can do better