Automation and the Advent of Super-Human Machine Interfaces • Fluidity
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Automation and the Advent of Super-Human Machine Interfaces

The Automation Buzz

Automation is everywhere in the media, and the excitement for our collective futures with it is warranted. Being able to cruise more safely behind the wheel of your Tesla on the interstate, if you’re so fortunate to own one, foreshadows much broader use in mobility. This certainly extends to the skies overhead. However, relinquishing complete control is still a ways off, which is why advances in human-machine interfaces will continue to be critical.

I recently had the amazing honor and thrill to take a training flight in the venerable F-16D “Viper,” a throttle- and joystick-piloted supersonic aircraft, up against an F-35 “Panther” in a training dogfight. While this amazing aircraft first took to the skies in the late 1980s, it remains an extraordinary example of American technological prowess. The aircraft has retained its lethality with successive innovations in automation, with highly skilled pilots still very much in control of its many systems and flight path. Pulling up to 9-Gs while tracking an adversary aircraft can only be accomplished if the aircraft becomes an extension of the pilot’s mind and body, accomplished through elements of onboard processing and rigorous training.

Having a Pilot in the Loop Remains Critical

Elon Musk, founder of SpaceX and Tesla, was a recent guest during a recent US Airforce “fireside chat” series. According to Aviation Week, he sat on the Air Force Association’s (AFA) stage and surprisingly declared that that the fighter aircraft—for decades the heart of the Air Force’s tactical combat capability—is already irrelevant. “The fighter-jet era has passed,” he told a room filled with pilots and airmen. Musk, known for his bullish and disruptive predictions on automation, clarified via Twitter in a reply to Aviation Week that both aircraft and pilot remain relevant. “The competitor [to an onboard piloted fighter] should be a drone fighter plane that is remote-controlled by a human, but with its maneuvers augmented by autonomy”, he wrote. While I personally don’t see our talented American fighter pilots leaving their cockpits anytime soon, they’ll certainly benefit from greater automation. Moreover, I can certainly see a day when telerobotically-controlled “sidekick” aircraft help them continue to rule the skies.

While the pace of drone operations is likely to remain much more docile (and subsonic) than fighter jet aircraft, automation has an enormous role in the UAS industry. This is apparent in many applications from asset inspection to security monitoring, and especially when considering Beyond Visual Line of Sight (BVLOS) missions. Edge computing, highly accurate GPS localization and onboard collision avoidance systems allow for safe, repetitive missions to be flown across a wide range of applications, and software to plan, execute and monitor these flights is advancing rapidly.

Having a “pilot in the loop” remains a critical element in flight safety, though, especially under dynamic, unscripted conditions. The strong winds and thermal updrafts of a raging fire, the unpredictability of movement of people and the unavoidable failure of technology at inopportune times require a capable pilot at the helm to take over in an emergency. Similarly, routine security or infrastructure flights that discover something out of the ordinary may require a closer look, probably better performed by the individual actually seeking that different perspective. And, with an automated swarm of drones used in a security mission, having the ability for one drone to be manually piloted should a sticky situation arise, while the rest of the swarm continues its work, could be the difference of a successful mission or not.

Simplifying the Translation of Human Intent

One of the largest stumbling blocks to more widespread use of drones is a limitation in the number of skilled pilots capable of flying in all conditions. Accounting for the obstacles and threats in their environment, while using traditional twin-stick controllers is an incredible challenge. It takes hundreds if not thousands of hours to attain true mastery of any complex skill, as Malcolm Gladwell (author of “Outliers”) will tell you. Parsing the four degrees of freedom camera drones use into two sticks is not how the mind is mapped to the real world.  The result is a tendency to over- or under-correct flight inputs, and to lose situational awareness, especially with challenging flight conditions.

Advances in human-machine interfaces like the FT Aviator drone controller simplify translation of human intent – where we want to go – to direct action – precisely how and where we want our drone to fly. Leveraging a single reference point on our body, the thumb, and providing visual and tactile feedback to inform the pilot when a command is being made and when it is not, FT Aviator pilots quickly develop a keen sense of “being onboard the drone”. This allows focus on what’s being filmed, not the mechanics of how to get there. We’ve seen complete novices pick up the FT Aviator and within a few moments of simple instruction are able to perform complex maneuvers and track moving targets on the ground. These tasks would require high-time, expert pilots’ full attention while using conventional sticks. 

Automation + Human Machine Interfaces = Evolution

Like an aerial dogfight under high-Gs, flying a drone in high wind, low contrast visibility or in unfamiliar airspace can be a real challenge. Automation will continue to offload some of this workload that drone pilots face, but skilled pilots will continue to be necessary to quickly and easily step in as conditions warrant. Technologies like Fluidity’s FT Aviator will give pilots ease of mind when flying under the most demanding circumstances, whether flown entirely by hand, or stepping in on an automated flight path during an emergency.

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