Black Swift applies machine vision and AI to unmanned aircraft

BOULDER — Black Swift Technologies LLC, a specialized engineering firm, has completed the first phase of a NASA-funded project using onboard sensors to develop a terrain-following unmanned aircraft system.

The project combines artificial intelligence and machine learning with a fixed-wing Black Swift A2 unmanned aircraft. The goal is to have autonomous, active navigation around obstacles and over rough terrain, done by the aircraft itself.

“Our state-of-the-art sensor suite and approach to sensor fusion enables a number of capabilities not yet seen for fixed-wing UAS,” Jack Elston, CEO of Black Swift Technologies, said in a prepared statement. “Integration of these developments with our highly capable avionics subsystem can make flying a fixed-wing small UAS significantly safer for operations in difficult terrain or beyond line of sight.”

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Using a fixed-wing aircraft was important to the project, Black Swift said in its news release, because they can scan more area than a multi-rotor aircraft. Still, sensing obstacles such as

trees and towers could be difficult, which can cause collisions. Black Swift’s solution fuses machine vision technologies with advanced sensors — including lidar and radar — that allowed the aircraft to operate safely in a variety of conditions.

There are now plans to extend the capabilities to multi-rotor aircraft and other unmanned platforms.