Launched in January 2013,[1] the project is part of the Interministerial Fund program of Aerospace Valley, a business cluster in southwestern France.

[2] With a budget of over one million euros,[3] Air-Cobot aims to develop an innovative collaborative mobile robot, autonomous in its movements and able to perform the inspection of an aircraft with nondestructive testing sensors during preflight or during maintenance operations in a hangar.

[4][13] The human operator's eyes fatigue over time while an automatic solution ensures reliability and repeatability of inspections.

The off-road platform, equipped with four-wheel drive, can move at a speed of 2 metres per second (7.2 kilometres per hour (4.47 mph)).

When visible, painted lanes on the ground can provide complementary data to the positioning system to have safer trajectories.

[A 1][A 5] Near the aircraft, a point cloud in three dimensions is acquired by changing the orientation of the laser scanning sensors fixed on pan-tilt units.

After filtering data to remove floor- or insufficiently large dot clusters, a registration technique with the model of the aircraft is used to estimate the static orientation of the robot.

An algorithm provides a real-time position estimation of the robot when enough elements from the landing gears and engines are visible.

During the evolution of the robot, these visual elements are extracted from a three-dimensional virtual model of the aircraft and projected in the image plane of the cameras.

The detection and monitoring are better in the two-dimensional laser data, while identification is easier in the images from the cameras; the two methods are complementary.

It can stop and wait for a gap in traffic, or avoid an obstacle by using a technique based on a spiral, or perform path planning trajectories.

The first part was focused on the simultaneous localization and mapping with an extended Kalman filter that estimates the state of a dynamic system from a series of noisy or incomplete measures.

Image analysis is used on doors to determine whether they are open or closed; on the presence or absence of protection for certain equipment; the state of turbofan blades or the wear of landing gear tires.

The evaluation is based on indices such as the uniformity of segmented regions, convexity of their forms, or periodicity of the image pixels' intensity.

By comparing the data acquired to the three-dimensional model of the aircraft, algorithms are able to diagnose any faults in the fuselage structure and provide information on their shape, size and depth.

Technical readjustment between the model of the aircraft and the scene point cloud is already used in navigation to estimate the static placement of the robot.

It is planned to make targeted acquisitions, simpler in terms of movement, to verify the absence of chocks in front of the landing gear wheels, or the proper closing of engine cowling latches.

Equipped with laser sensors and high resolution camera, the drone performs autonomous flight around the aeroplane.

[19] Founded in 2015, Donecle, a Toulouse start-up company, has also launched a drone approach which was initially specialized in the detection of lightning strikes on aeroplanes.

A damage report is sent on the operator's touch pad with each area of interest and the proposed classification with a probability percentage.

[21] In 2015, in an interview given to the French weekly magazine Air & Cosmos, Jean-Charles Marcos, chief executive officer (CEO) of Akka Research, explained that once developed and marketed the Air-Cobot should cost between 100,000 and 200,000 euros.

[22] The same month, the Singapore government enlisted Airbus Group to help local maintenance, repair, and operations providers to stay competitive against neighbour countries like Indonesia, Thailand and the Philippines which are cheaper.

[A 2] In addition of Air-Cobot, a previous step in this research axis is Co-Friend, an intelligent video surveillance system to monitor and improve airport operations.

[A 2][24] Futur researches will focus on the management of this operations, autonomous vehicles, non-destructive testing and human-machine interactions to increase efficiency and security on airports.

[30] Part of publications is centered on navigation and/or inspection by Air-Cobot while the rest focuses on specific numerical methods or hardware solutions related to the issues of the project.

During the international conference Machine Control and Guidance (MCG) of 2016, the prize for the best final application is awarded to the authors of the publication Human-robot collaboration to perform aircraft inspection in working environment.

[31] On 17 April 2015, Airbus Group distributed a project presentation video, made by the communication agency Clipatize, on its YouTube channel.

[33] Located at Laboratoire d'analyse et d'architecture des systèmes during development, researchers or engineers working on the project regularly present a demonstration to visitors (external researchers, industrial partners, or students); it was also demonstrated to the general public during the 2015 Feast of Science.

[34] Airbus Group, on 17 February 2016, broadcast a YouTube video presentation of its vision of the hangar of the future in which it plans to use Air-Cobot.