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Del curso dictado por University of Pennsylvania

Robotics: Aerial Robotics

1748 calificaciones

University of Pennsylvania

Robotics: Aerial Robotics

1748 calificaciones

Curso 1 de 6 en SpecializationRobotics

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.

De la lección

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.

Unmanned Aerial Vehicles7:08

Key Components of Autonomous Flight1:29

State Estimation7:34

Applications3:43

Meet the TAs0:52

Conoce a los instructores

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

Before we end this module, I'd like to leave you with a flavor of some of

the applications in this area, and also some of the drivers for the UAV industry.

Lets first start with agriculture.

In our lab, we're using robots like this and apple orchards

to see how we can improve the efficiency of production with specialty crops.

So robots like this are able to patrol orchards flying between the crops and

over the crop lines, getting three dimensional information about

every plant and fruits growing on the plant.

If you look at the three maps on the bottom,

the one on the bottom left is obtained using infrared imagery.

The one on the bottom right is obtained by using

the laser sensor on top of the robot and cameras.

It represents three dimensional information and

give you volume metric information about every plant.

The one at the bottom middle is the NDVI map,

which essentially tells you a little about the vigor of every plant.

And in operations like this, we try to use multiple vehicles.

Again, if you wanna cover a large area in a short period of time,

it makes sense to use multiple vehicles cooperating with each other,

collecting this information in real time.

So vehicles like this can get information that can change the way we think about

precision farming, allowing farmers to get models of individual plants,

recognizing which plants need special attention.

Getting estimates for yield and determining which plants to water and

at what time during the year.

Robots like this are finding application in the construction industry.

They're able to acquire three-dimensional maps of buildings as they're being built.

This allows the owner of the building to monitor progress,

comparing the progress to specifications.

And also plan for

resource allocation during the construction of these buildings.

Robots like this are being used in archaeology to get

three dimensional information about historical sights.

Landscapes, getting information about buildings that were built

several thousand years ago.

They're being used for photography, to take breathtaking pictures,

obtaining vistas that could not be obtained by human held cameras.

Robots like this can be used as first responders.

These experiments being conducted in our laboratory where we see a swarm of drones

rushing to a spot where there might be an emergency or

perhaps where there's been a 911 call.

Robots like this can respond before human first responders get to the site.

And they can be used to construct three dimensional maps

by surrounding buildings of interest.

On the top left you see trajectories being planned autonomously.

On the top right, you see a mosaic being constructed in real time.

And on the bottom,

you see a three dimensional reconstruction of the site that needs attention.

Again, the idea is that you would get this information and provide human first

responders with situational awareness well before they get to the scene.

So they're better equipped and they don't get into harms way.

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