BU Researcher Using Drone Racing to Train AI

In a case of where racing, in this case. Drone Racing has been able to advance the general state of the industry Boston University researchers are using competitive drone racing as a testing ground to advance AI-controlled flight.

Wil Koch a researcher as Boston University,  was hooked on racing and the use of FPV, “You put the goggles on and they allow you to see live video transmitting from a camera mount on the drone,” Koch says. It is “by far, the coolest thing.”

In an article originally published at Boston University’s’ website.  As a result of a passion for drone racing, and with their background as a researcher,  Will in conjunction with Boston University created Neuroflight.  Which has it’s mission as:

“Little innovation has been made to low-level attitude flight control used by unmanned aerial vehicles, which still predominantly uses the classical PID controller. Although PID control has demonstrated exceptional performance, it has its limitations, such as its inability to adapt to change. Our mission is to research, design and develop deep neural network based flight controllers for high-precision applications.”

Here is what it does.

The Neuroflight controller, Koch says, is trained in computer simulation to adapt to a wide range of different events, correcting the drone’s position inside a dynamic and changing, albeit digital, environment. After simulation training, the “educated” neural network goes to work in the real world by sending signals to the drone motors, telling them how to respond so that the quadcopter moves in the exact way that its operator intends.

“PID is a linear control system, but the environment is nonlinear,” says Koch, who is a College of Arts & Sciences graduate student in computer science. “We’re ripping out that PID controller and dropping in a trained neural network.”

Here is a video of Neuroflight in action:

 

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