Learn about how to make mobile robots move in effective, safe, predictable, and collaborative ways using modern control theory. This course investigates how to make mobile robots move in effective, safe, and predictable ways. The basic tool for achieving this is "control theory", which deals with the question of how dynamical systems, i.e., systems whose behaviors change over time, can be effectively influenced. In the course, these two domains - controls and robotics - will be interleaved and we will go from the basics of control theory, via robotic examples of increasing complexity - all the way to the research frontier.
The course will focus on mobile robots as the target application and problems that will be covered include (1) how to make (teams of) wheeled ground robots avoid collisions while reaching target locations, (2) how to make aerial, quadrotor robots follow paths in the presence of severe disturbances, and (3) how to locomotive bipedal, humanoid robots.
While the main focus of this course is theory, it is important to be able to map the theory onto an actual physical platform. As such, the course will provide detailed instructions on how to build a mobile robot from scratch as an optional part of the course. In addition, an introduction into microcontrollers, mechatronics, and electronics will be given so that, by the end of the course, the controllers developed in the course can run on an actual mobile robot.
The course will also feature optional programming assignments, which will focus on implementing the controllers developed in this course for a mobile robot. A MATLAB-based simulator will be available run controllers from the programming assignments on a simulated robot or on the mobile robot built in this course. As a result of support from MathWorks, a downloadable license for MATLAB and course recommended toolboxes will be available for the duration of the MOOC.
We are delighted to launch Control of Mobile Robots - a course that focuses on the application of modern control theory to the problem of making robots move around in safe and effective ways. The structure of this class is somewhat unusual since it involves many moving parts - to do robotics right, one has to go from basic theory all the way to an actual robot moving around in the real world, which is the challenge we have set out to address through the different pieces in the course:
Lectures - here Magnus Egerstedt will discuss modern control theory as it applies to robotics. They will at times be rather math-heavy but this is due to the fact that control theory is by its very nature mathematical, yet remarkably applicable.
Programming & Simulations - to implement the course material in simulation, we are making our own robot simulator, that we use in class at Georgia Tech as well as for our research at the GRITS Lab, available. The simulator runs on MATLAB, which is available to all students for the duration of this course. Instructions for accessing MATLAB (and any other information regarding the programming assignments) is available under the Programming Assignments tab. Jean-Pierre de la Croix will be providing weekly programming & simulation videos, and support for automatic grading of the assignments is also provided. Note that this part of the course is optional and does not contribute to the pass/fail grade. It is to be thought of as a service to make the experience richer.
Robots - Finally, we struggled quite a bit with how to structure a course that would benefit significantly from actual hardware. Our solution is to provide weekly hardware videos - lead by Rowland O'Flaherty - that shows how to build your own robot and then deploy the control code you have developed on the simulator.
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