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.
Ce cours fait partie de la Spécialisation Robotique
Robotics: Aerial Robotics
proposé par
Compétences que vous acquerrez
Programme du cours : ce que vous apprendrez dans ce cours
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.
Geometry and Mechanics
Welcome to Week 2 of the Robotics: Aerial Robotics course! We hope you are having a good time and learning a lot already! In this week, we will first focus on the kinematics of quadrotors. Then, you will learn how to derive the dynamic equations of motion for quadrotors. To build a better understanding on these notions, some essential mathematical tools are discussed in supplementary material lectures. In this week, you will also complete your first programming assignment on 1-D quadrotor control. If you have not done so already, please download, install, and learn about Matlab before starting the assignment.
Planning and Control
Welcome to Week 3! We have developed planar and three-dimensional dynamic models of the quadrotor. This week, you will learn more about how to develop linear controllers for these models. With this knowledge, you will be required to complete the second programming assignment of this course, which focuses on controlling the quadrotor in two dimensions. We encourage you to start working on the assignment soon. This week ends with a discussion on motion planning for quadrotors.
Advanced Topics
Welcome to Week 4! So far, we have gone over the basics of developing linear controllers for quadrotors and motion planning. In this last week of the course, we will discuss some more advanced material on how to enable quadrotors to perform more agile maneuvers and to operate autonomously in teams. Note that the last programming assignment on quadrotor control in three dimensions uses material from the previous weeks. It is strongly recommended to start the assignment as soon as possible.
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Principaux examens pour Robotics: Aerial Robotics
The course is very good.\n\nThe classes are well taught and show general concepts. It is necessary to do research on the internet, to solve the assignments. This is not a bad thing in my point of view
I think this is very good course of aerial robotics research. Being a student of robotics, I feel that some of stuffs in this course needs a good background in control and mechanical engineering.
Enseignant
Vijay Kumar
Nemirovsky Family Dean of Penn Engineering and Professor of Mechanical Engineering and Applied MechanicsÀ propos de Université de Pennsylvanie
À propos du Spécialisation Robotique
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