Chevron Left
返回到 Motion Planning for Self-Driving Cars

学生对 多伦多大学 提供的 Motion Planning for Self-Driving Cars 的评价和反馈

4.8
400 个评分
74 条评论

课程概述

Welcome to Motion Planning for Self-Driving Cars, the fourth course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main planning tasks in autonomous driving, including mission planning, behavior planning and local planning. By the end of this course, you will be able to find the shortest path over a graph or road network using Dijkstra's and the A* algorithm, use finite state machines to select safe behaviors to execute, and design optimal, smooth paths and velocity profiles to navigate safely around obstacles while obeying traffic laws. You'll also build occupancy grid maps of static elements in the environment and learn how to use them for efficient collision checking. This course will give you the ability to construct a full self-driving planning solution, to take you from home to work while behaving like a typical driving and keeping the vehicle safe at all times. For the final project in this course, you will implement a hierarchical motion planner to navigate through a sequence of scenarios in the CARLA simulator, including avoiding a vehicle parked in your lane, following a lead vehicle and safely navigating an intersection. You'll face real-world randomness and need to work to ensure your solution is robust to changes in the environment. This is an intermediate course, intended for learners with some background in robotics, and it builds on the models and controllers devised in Course 1 of this specialization. To succeed in this course, you should have programming experience in Python 3.0, and familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses) and calculus (ordinary differential equations, integration)....

热门审阅

KN
Nov 30, 2020

If not online and self-paced, I would not have the courage to attempt this advanced-level Self-Driving Program. Thanks UoT and the instructors for offering such high-quality courses to the public. 👍😊

YY
Feb 4, 2020

The course is very good for the basic knowledge of self driving. There are a lot of good examples of different parts. I have learned a lot from it. Thank you for your excellent job!

筛选依据:

51 - Motion Planning for Self-Driving Cars 的 73 个评论(共 73 个)

创建者 MIHIR R J

Jun 13, 2020

Quite Informative!

创建者 Anis M

May 24, 2020

simply , the best!

创建者 Ramyashree A H

May 30, 2020

Wonderful course

创建者 Soumyajit M

Oct 9, 2020

Great Course

创建者 Akib C

Aug 24, 2020

Thanks a lot

创建者 Matías F

Jan 18, 2021

amazing!

创建者 AmirHossein H

May 9, 2019

perfect

创建者 Yusuf O Y

Dec 26, 2020

Thanks

创建者 Jeff D

Nov 28, 2020

Thanks

创建者 Md. R Q S

Aug 21, 2020

great

创建者 Miguel P M

Jan 16, 2021

The final project could've been a little shorter in terms of complexity and rather specific sub exercises regarding each module could've been planned. This is because most of the TODOs were pretty self explanatory and left little margin for putting hands on workin on path optimization, etc. I understand and agree this is very difficult to plan out, and I take away from this specialization a great deal, though!

创建者 Sean B

Oct 1, 2020

Excellent material and there is a ton of supplemental links to check out. Many of the assignments do not have intermediate checks so debugging is a challenge. Also there is very little active support, there aren't any instructors active in the forums currently so I had to rely on old discussion posts. Still, I made it through with a large new skill set to show for it.

创建者 Artod d

Sep 28, 2021

Honestly, I thought that AI methods are more involved in the motion planning for self-driving cars... About the course, the final assignment is super easy compared to previous assignments in the specialization.

创建者 陈然

Jul 2, 2020

Although it took me a long time to finish the Programming Assignments, somehow i feel its not hard enough. LOL.

创建者 Brike

Mar 20, 2021

Excellent lesson!

I hope this course could provide some coding homework written in C++.

创建者 吕吉冬

May 8, 2019

Too many errors in slides and a little bit easy.

创建者 Igor S

Nov 6, 2019

Good lectures, but badly prepared assignments.

创建者 Liviya v

Jan 1, 2021

goog course

创建者 Dane R

Aug 29, 2020

The material covered was good, and the supplemental materials are always helpful to guide those that want to learn more (I am a huge fan of these references being provided, even if we have to hunt down a PDF).

I think this course was missing more coding exercises though. This is a deep subject, and a critical one in the AV world, so I'm very disappointed that there weren't more of these to illustrate how to solve some common motion planning problems.

The final project is also very weak. I understand that motion planning is very complex and involves a lot of math (making it difficult to create an assignment that isn't overwhelmingly difficult), but the final assignment is full of hand-holding, making already easy tasks trivial. Most of the interesting parts are already done for you, so I didn't have to think about motion planning at all. On top of that there is an error in the Coursera-provided code which students have pointed out a year ago, yet still exists. Fix this!

I think this course is worth doing if you are pursuing the Self Driving Car curriculum, and it has some solid information in it, but just don't expect to get rich coverage. The first 3 courses in the Self Driving Cars curriculum were much better.

创建者 Shaun B

Aug 27, 2020

I wish there were more coding assignments in weeks 1-6. I also wish that the final assignment had more code for us to write. For example, collision_checker.py has <5 lines of code to be written.

创建者 Patrick N

Jul 26, 2020

Final Test is a stupid reverse engineering and integration task without demand for deeper knowledge

创建者 Genius Z

Jun 21, 2020

TOO HIGHLEVEL

创建者 Kasra D

May 13, 2021

This course is good for you if you already know the concepts and just want to review it. It's a terrible course if you don't know the concepts and want to learn from it. This is true for all courses in this specialization.