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Iris Automation Detect-and-Avoid System Earns Second BVLOS Waiver and Trust of FAA

BY Isabella Lee
22 August 2019

Two participants in the FAA UAS Integration Pilot Program (UAS IPP) have received approval to conduct beyond visual line of sight drone operations using detect-and-avoid technology in place of a visual observer (VO). Both approvals were granted from the FAA based on Iris Automation’s proven collision avoidance system.

Iris Automation Casia DAA System

Image Source: Iris Automation

The approvals were given to the University of Alaska Fairbanks and the Kansas Department of Transportation—both are UAS IPP participants.

“This marks a huge advancement in the FAA UAS Integration Pilot Program and the drone industry,” said Iris Automation CEO and Co-founder Alexander Harmsen. “This is the first time detect-and-avoid technology is approved by an aviation authority as reliable enough to allow for BVLOS drone operations.”

Historically, all FAA-issued Part 107 BVLOS waivers have required some ground-based visual observer to mitigate the risk of non-cooperative aircraft entering the mission area—an expensive and unscalable restriction on the use of drones for commercial purposes.

About the Two BVLOS Missions

The two operations mark the first instances in which the FAA approved BVLOS operations without requiring a VO to observe the airspace and detect/track all air traffic or hazards. Instead, Iris Automation’s Casia system was deemed sufficient to monitor potential hazards in the airspace.

Prior to these two flights, the FAA approved a similar BVLOS waiver to Airobotics, permitting the company to fly their automated drone out of sight of the VO; however, the VO was still required to observe the airspace to detect and track all other air traffic or hazards.

University of Alaska Fairbanks – 3.87-mile BVLOS flight without VO

The U.S. Department of Transportation selected The University of Alaska Fairbanks (UAF) as one of just 10 participants in the nationwide UAS IPP. The program allows state, local and tribal governments to work with drone operators and manufacturers to speed up the safe entry of unmanned vehicles into the nation’s airspace beyond what is currently permissible under the FAA Part 107 regulations. The UAF team proposed several ways to pioneer safe drone use in Alaska—to deliver medical devices to remote areas, help searches and rescues, survey fish and wildlife, and monitor pipelines, roads and other infrastructure.

The UAF team used the BVLOS waiver to inspect a 3.87-mile stretch of Trans-Alaska Pipeline infrastructure. The flight was conducted on Wednesday, July 31, 2019.

University of Alaska BVLOS Flight

Nick Adkins, director of operations for ACUASI (left) and Troy Mestler, pilot and CEO of Skyfront (right), celebrate the completion of the BVLOS flight. The Skyfront Perimeter hybrid UAV used in the flight sits on the ground. Image Source: UAF photo by Sean Tevebaugh.

The mission was flown using Skyfront long-range hybrid electric drones leveraging Iris Automation’s onboard detect-and-avoid systems and eight Echodyne ground-based radars.

With Iris Automation and Echodyne sensor technologies, routine commercial missions like linear inspection and medical deliveries to remote communities are both practical and safe.

Eben Frankenberg, CEO and Founder, Echodyne

Kansas Department of Transportation – 9-mile BVLOS flight without VO or Ground-Based Detection

Following the UAF waiver, the Kansas Department of Transportation was granted a BVLOS waiver that established another series of firsts for the drone industry.

In a collaborative effort between Kansas State University Polytechnic Campus (K-State Polytechnic), Westar Energy, Iris Automation, and KDOT, the Kansas IPP team gained approval to fly a nine-mile track to evaluate technologies for powerline inspections in rural Kansas.


This is the first drone flight in history to leverage onboard sense and avoid systems alone for collision avoidance. It also marks the first required automated avoidance action. This is different from previous waivers using ground-based systems, where the remote pilot has been responsible for taking the avoidance maneuver.

This approval is the first of its kind for long line linear infrastructure and is the first step to enable routine commercial infrastructure inspection across the state.

The ability to fly BVLOS missions without ground-based radar or visual observers is a significant advancement…this waiver allows the Kansas IPP team the ability to research and develop truly scalable BVLOS UAS operations for the automated inspection of linear infrastructure.

— Mike Kelly, Senior UAS Coordinator, Westar Energy

As the second waiver approval leveraging Iris Automation’s detect-and-avoid technology, the approval demonstrated a level of trust in the Iris system on behalf of the FAA.

The FAA is trusting us to pave the way for a safer, scalable future together with this precedent-setting second approval of our system.

— Alexander Harmsen, CEO and Co-Founder, Iris Automation

[Read our interview with Iris Automation CEO Alexander Harmsen here.]

About Iris Automation’s Detect-and-Avoid System

The Iris Automation Casia system is a turnkey solution that detects, tracks and classifies other aircraft and makes intelligent decisions about the threat they may pose to the vehicle, and triggers automated maneuvers to avoid collisions. The tool can work in coordination with ground-based sensors such as Echodyne’s innovative MESA radar technology, which has been used at a number of FAA UAS test sites.

The Casia technology has been extensively tested globally, with 7,000+ real-world test flights and mid-air collision scenarios–flying various manned aircraft against UAS–and over 40,000 encounters in simulation.

The drone industry is seeing growing means to conduct flights outside the limitations of FAA Part 107 regulations. The latest Iris Automation approval is just one of many successes to emerge from the UAS IPP. Share your thoughts on the progress made by UAF, KDOT, and other UAS IPP participants in this thread in our community forum.

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