Tests for UAS Integration Pilot Program begin – Iris Automation

SALINA – The Kansas Department of Transportation is starting the testing phase of the

Integration Pilot Program this week. Flights by Iris Automation will focus on enabling new detect

and avoid capabilities for drones.

Iris Automation will be testing its collision avoidance technology in the airspace above Gypsum’s farmlands. The technology uses computer vision and artificial intelligence to allow drones to see

the world the way a pilot does, enabling beyond visual line of sight flights. Test flights will take

place throughout the week, and the technology will be evaluated through controlled drone flights

against a manned aircraft.

“The flights we will conduct this week are a crucial part of the overarching strategy to further

UAS representation as an important economic contributor for Kansas,” said Bob Brock, KDOT

Director of Aviation. “We’re excited to continue our partnership with Iris Automation and our

other IPP Team Members as we look forward into the future.”

The Integration Pilot Program was implemented by the Federal Aviation Administration through

a Presidential Memorandum. KDOT was selected as one of 10 government organizations to test

how drones can fly safely over people, at night and beyond visual line of sight, which will open

new uses with industries for drones in the future. These tests are designed to help the FAA

develop regulations for these activities.

“At Iris Automation, our cutting-edge technology is unlocking the potential of drones by enabling

them to fly beyond visual line of sight,” said Alexander Harmsen, Chief Executive of Iris

Automation. “I am delighted to be putting it to the test with Kansas Department of

Transportation.”

Iris Automation’s detect and avoid technology has already been tested in thousands of collision

scenarios, designed and executed by the company’s flight test team in Nevada. The technology

uses a camera, processor and computer vision software to see the airspace around the drone in

real-time, enabling collision avoidance. The software classifies and tracks moving objects and

identifies their speed and direction in relation to the drone it is attached to. The system acts as a

high-level supervisor to the drone’s autopilot, instructing it to execute automated avoidance

maneuvers where necessary and informing the remote pilot in command of emergency

situations.

http://www.irisonboard.com

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