AI Case Study

DARPA simulates flight and landing of Boeing 737 by an AI-driven robot co-pilot

DARPA has announced the successful simulated flight and landing of a Boeing 737 by an AI-driven robot co-pilot named ALIAS, which is an acronym for Aircrew Labor In-Cockpit Automation System. The system was build by Aurora Flight Sciences and consists of cameras, machine learning technology and a robotic arm capable of operating all of the cockpit’s controls.

Industry

Industrials

Aerospace And Defence

Project Overview

"“ALIAS” is an acronym for “Aircrew Labor In-Cockpit Automation System.” ALIAS was built for DARPA by Aurora Flight Sciences, 'a leader in the development and manufacturing of advanced unmanned systems and aerospace vehicles,' according to their website. It goes far beyond existing autopilot systems that are limited to assisting a human pilot in flying a plane in-between the critical takeoff and landing phases.

ALIAS has, broadly speaking, three components:

* A camera that can see and read all of the cockpit’s instruments and gauges
* AI-driven software that uses machine learning to acquire the knowledge needed to operate the aircraft. It also has access to a database of knowledge gained by other ALIAS installations
* A robotic arm that can operate all of the cockpit’s controls, and thus the plane

Reported Results

Successful simulated flight and landing of a Boeing jet

Technology

Advanced unmanned system
"AI-driven software that uses machine learning to acquire the knowledge needed to operate the aircraft."

Function

Information Technology

Development

Background

Benefits

Data