A new entrant to the aircraft drone inspection space is targeting the commercial launch of its Drone-as-a-Tool (DaaT) solution this year as the aviation industry’s recovery begins. Netherlands-based Mainblades is continuing demonstrations this month with customers in Europe to finish testing and validating its technology after progress was delayed by the COVID-19 pandemic.

“Having been sidelined several times due to technology immaturity, drones are now being re-examined to solve crucial COVID-19 challenges,” says Dejan Borota, co-founder and CEO, Mainblades. According to Borota, the aviation industry has been late to the game with regard to increasing efficiency through digitalization compared to other industries, regarding innovation more as a playground for experiments instead of as a necessity to stay competitive. “The COVID-19 crisis has recalibrated everybody in the aviation industry, forcing airlines, MROs and OEMs to really look toward innovation for real-world, direct-to-be-implemented, cost-saving solutions,” he adds.

In addition to the efficiency and accuracy gains drone inspections can provide (Mainblades’ DaaT solution claims to perform full aircraft inspection and reporting on a narrowbody aircraft in approximately two hours), Borota notes that the technology also lends itself well to more remote working models seen during the pandemic. According to Mainblades, its technology enables efficient collaboration between MROs and third parties by making it possible for engineers to perform inspections remotely based on the data captured by the drone at the hangar.

While there are several aircraft drone inspection providers already on the market, Borota says Mainblades provides a unique value proposition, thanks in part to its robotics expertise. The DaaT solution uses robotics technology for its software paired with LiDAR sensors to localize, map, navigate and plan in a way that gives it what Mainblades calls the industrial inspection drone equivalent of a human’s brain and eyes.

The hardware system of Mainblades’ DaaT solution is modular, so it can be retrofitted to different types of drones. The current offering is built on an industrial-grade drone from DJI, which Mainblades says enables it to keep up with fast-paced developments in the drone industry. It says its solution is also able to perform inspections both inside and outside the hangar on any type of aircraft due to enhancements it made to its LiDAR-based algorithm using GPS data, and by accounting for external factors such as strong winds. While stringent airport regulations are still a challenge standing in the way of outdoor drone inspections, Mainblades is working to gain certification from FAA and EASA, as well as certification as part of OEM aircraft maintenance manuals.

Mainblades has been developing its solution with support from Corendon Airlines, JetSupport and KLM, the latter of which it has been working with since before the startup’s official launch in 2017. In addition to its planned demonstrations with companies in Europe, Mainblades is also in talks with companies in the U.S., Latin America and Asia about setting up pilot projects. Borota notes that although aviation budgets have been tight—especially during the beginning of the pandemic—the situation has actually opened doors for talks with more prospective customers.

Borota says Mainblades has also found broader interest in drone inspections within other segments of aviation, such as cargo airlines, paint providers, independent MROs and lessors—which are facing a glut of inspection work in the next couple of years due to aircraft ownership changes during the pandemic.

The Mainblades solution comes with all of the hardware and software items needed for complete inspection of any aircraft, including a drone equipped with a camera, sensors and batteries, a remote controller, a battery charging station, and an iPad equipped with its software and web portal for remote access and storage. According to Mainblades, the solution can be ready for operation within five minutes after unboxing.