瀏覽 Coursera 的全部課程

For Enterprise

Join for Free
Log In

艺术与人文
商务
计算机科学
数据科学
信息技术
健康
数学和逻辑
个人发展
物理科学与工程
社会科学
语言学习
學位
證書

瀏覽 Coursera 的全部課程

瀏覽
搜索
企業版
登錄
免費加入

Effects of Size

Loading...

Robotics: Aerial Robotics

宾夕法尼亚大学

4.5（2,041 個評分） | 80K 名學生已註冊

課程 1（共 6 門，机器人專項課程）

How can we create agile micro aerial vehicles that are able to operate autonomously in cluttered indoor and outdoor environments? You will gain an introduction to the mechanics of flight and the design of quadrotor flying robots and will be able to develop dynamic models, derive controllers, and synthesize planners for operating in three dimensional environments. You will be exposed to the challenges of using noisy sensors for localization and maneuvering in complex, three-dimensional environments. Finally, you will gain insights through seeing real world examples of the possible applications and challenges for the rapidly-growing drone industry. Mathematical prerequisites: Students taking this course are expected to have some familiarity with linear algebra, single variable calculus, and differential equations. Programming prerequisites: Some experience programming with MATLAB or Octave is recommended (we will use MATLAB in this course.) MATLAB will require the use of a 64-bit computer.

查看授課大綱

您將學習的技能

Motion Planning, Robotics, Quadcoper, Matlab

審閱

4.5（2,041 個評分）

5 stars
1,393 ratings
4 stars
471 ratings
3 stars
97 ratings
2 stars
41 ratings
1 star
39 ratings

CG

Feb 12, 2016

Well balanced mix of theory and practical applicability. Explanation of the material is also very good.\n\nThe assignments are nicely built on the taught material to stimulate understanding.

UM

Apr 08, 2019

The course is very good and is designed such that even beginners can get a good grasp on the content that is made available. The discussion forums are great and help in making life easier.

從本節課中

Introduction to Aerial Robotics

Welcome to Week 1! In this week, you will be introduced to the exciting field of Unmanned Aerial Robotics (UAVs) and quadrotors in particular. You will learn about their basic mechanics and control strategies and realize how careful component selection and design affect the vehicles' performance. This week also provides you with instructions on how to download and install Matlab. This software will be used throughout this course in exercises and assignments, so it is strongly recommended to familiarize yourself with Matlab soon. Tutorials to help you get started are also provided in this week.

Basic Mechanics4:27

Dynamics and 1-D Linear Control10:29

Design Considerations3:37

Design Considerations (continued)4:33

Agility and Maneuverability7:00

Component Selection4:24

Effects of Size4:38

Supplementary Material: Introduction3:19

Supplementary Material: Dynamical Systems3:15

Supplementary Material: Rates of Convergence3:20

教學方

Vijay Kumar
Nemirovsky Family Dean of Penn Engineering and Professor of Mechanical Engineering and Applied Mechanics

腳本

Next I want to explore with you the effects of sizing the platform.

What does it mean to have a larger platform?

Well clearly it becomes bigger and becomes heavier, and

therefore the truss to weight ratio changes.

What does it mean to have a smaller platform?

Well, the truss to weight ratio might get better.

Or does it?

So there are a few things you might consider.

First the mass, the inertia of the platform.

The maximum amount of thrust it can exert and the maximum moment it can generate.

Lets look at the characteristic length l.

Which is roughly half the diameter of the vehicle.

If you look at the mass of the vehicle,

it scales as the cube of the characteristic length.

And the moments of inertia go as the fifth power of the characteristic length.

Very simply, mass scales as volume and volume goes as l cubed.

Moments of inertia go as mass times length squared, and

therefore it's scaled as l to the fifth.

If you look at the total thrust applied by the rotors,

this scales as the area spanned by a single rotor.

It also scales as the square of the blade hit speed.

So if omega is the rotor speed, and

r is the rotor radius, then the product of omega and

r gives you the blade hit speed and the thrust scales as velocity squared.

In short, the thrust scales as r squared times v squared,

where v now is the blade tip speed.

Let's now look at the moment that can be generated by a vehicle like this.

While clearly if you apply a thrust f on each rotor,

the moment that you can apply scales as force times length.

So if f is the thrust and

l is the characteristic length then the moment scales as f times l.

Now let's assume that the rotor size scales as a characteristic length.

And this is reasonable to do because this is a geometric constraint.

In this setting the thrust goes as l squared times v squared.

And the moment goes as l cubed times v squared.

Now let's look at the max acceleration and the max angular acceleration,

which we can calculate by taking the total thrust, dividing it by the mass and

the total moment and dividing it by the moment of inertia.

If you substitute the appropriate scaling rules, the mass going as l cubed,

the inertia going as l to the fifth,

you quickly realize that the maximum accelerations, linear and

angular, go as v squared over l and v squared over l squared.

How does the blade fit speed, v, scale as the character stick length?

Well, there are a couple of ways of looking at it.

If you look at the scaling experiments we've done in our lab, we've found that

the blade tip speed scales as the square root of the characteristic length.

So this is generally true at the scales that

we play around with in our laboratory.

These are smaller vehicles, and this might not hold for

much larger platforms like commercial helicopters.

This paradigm is often called Froude scaling.

In contrast to that,

in aerodynamics there's a different paradigm called Mach scaling.

So Froude scaling suggests that the blade tip speed goes as

the square root of length.

Mach scaling suggests that the blade tip speed is roughly constant,

independent of length.

With these two assumptions, you can calculate the maximum thrust,

in one case it goes as l cubed and the other case it goes as l squared.

And you can calculate the maximum acceleration and

the maximum angular acceleration.

In both cases you will see that the angular acceleration

increases as you scale down the size of the platform.

And this in fact results in greater agility.

So, that's really the key idea.

The smaller you make the vehicle,

the larger the acceleration you can produce in the angular direction.

And this allows greater agility.

探索我們的目錄

免費加入並獲得個性化推薦、更新和優惠。

Coursera 致力於普及全世界最好的教育，它與全球一流大學和機構合作提供在線課程。

© 2019 Coursera Inc. 保留所有權利。

通過 App Store 下載

通過 Google Play 獲取

Coursera
關於
管理團隊
工作機會
目錄
證書
MasterTrack™ 證書
學位
企業版
政府版

社區
Learners
Partners
Developers
Beta Testers
Translators

連接
博客
Facebook
領英
Twitter
Instagram
YouTube
技術博客

更多
條款
隱私
幫助
內容訪問
媒體
聯繫我們
目錄
附屬公司