Stanford engineers
are developing software to predict and prevent collisions
of unmanned
aircraft, including delivery drones, in congested urban airspace.
(December 10, 2015) When
Jeff Bezos unveiled his vision of drones delivering packages to Amazon
customers during a 60 Minutes segment in late 2013, it caught many people as
science fiction. Scarcely two years later, drones are poised to become a
technology for not just delivering packages, but monitoring agriculture,
gathering news in urban environments and even conducting search and rescue
missions.
But before drone aviation can become pervasive, a new
infrastructure must be developed to define low-altitude avenues of flight,
regulate traffic in congested areas and prevent collisions.
On this front, the Stanford Intelligent Systems Laboratory
(SISL) is part of a broad partnership led by NASA Ames to create an unmanned
aerial system traffic management system, or UTM, to manage the expected surge
in unmanned flights.
"UTM is meant to fulfill a lot of the functions of air
traffic control, but it will be in the cloud and largely automated," said
SISL Director Mykel Kochenderfer, an assistant professor of aeronautics and
astronautics.
NASA envisions that the UTM system will be able to support
the orchestration of a huge number of drone operations without air traffic
control operators monitoring each and every vehicle in the air. A key attribute
of this system will involve automated conflict avoidance – software that can
alert multiple drones when a collision is possible, and calculate the maneuvers
necessary to avoid it.
Kochenderfer recently coauthored a new paper with mechanical
engineering graduate student Hao Yi Ong in which they detail a
conflict-avoidance algorithm that, when implemented within the UTM system, will
minimize the threat of low-altitude, unmanned collisions.