page_title: Air-Cobot
section_title: Navigation around the aircraft
hierarchical_section_title: Air-Cobot / Autonomous navigation / Navigation around the aircraft
caption_attribution_description: F-GKXY A.320 Air France
context_page_description: Air-Cobot is a French research and development project of a wheeled collaborative mobile robot able to inspect aircraft during maintenance operations. This multi-partner project involves research laboratories and industry. Research around this prototype was developed in three domains: autonomous navigation, human-robot collaboration and nondestructive testing.
  Air-Cobot is presented as the first wheeled robot able to perform visual inspections of aircraft. Inspection robots using other types of sensors have been considered before, such as the European project Robair. Since the launch of the project, other solutions based on image processing began to be developed, such as EasyJet with a drone, the swarm of drones from Toulouse company Donecle and the Aircam project of the aerospace manufacturer Airbus.
  Since the beginning of the project in 2013, the Air-Cobot robot is dedicated to inspect the lower parts of an aircraft. In the continuation of the project, there is the prospect of coupling with a drone to inspect an aircraft's upper parts. In October 2016, Airbus Group launched its research project on the hangar of the future in Singapore.
context_section_description: To perform the inspection, the robot has to navigate around the aircraft and get to the checkpoints called up in the aircraft virtual model. The position of the aircraft in the airport or factory is not known precisely; the cobot needs to detect the aircraft in order to know its position and orientation relative to the aircraft. To do this, the robot is able to locate itself, either with the laser data from its laser range finders, or with image data from its cameras.
  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. The robot moves and holds this orientation by considering its wheel odometry, its inertial unit and visual odometry.
  Laser data are also used horizontally in two dimensions. An algorithm provides a real-time position estimation of the robot when enough elements from the landing gears and engines are visible. A confidence index is calculated based on the number of items collected by lasers. If good data confidence is achieved, the position is updated. This mode is particularly used when the robot moves beneath the aircraft.
  For visual localization, the robot estimates its position relative to the aircraft using visual elements (doors, windows, tires, static ports etc.) of the aircraft. 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 projected shapes are used for pattern recognition to detect those visual elements. The other detection method used is based on the extraction of features with a Speeded Up Robust Features (SURF) approach. A pairing is performed between images of each element to be detected and the actual scene experienced.
  By detecting and tracking visual landmarks, in addition to estimating its position relative to the aircraft, the robot can perform a visual servoing. Research in vision is also conducted on simultaneous localization and mapping (SLAM). A merger of information between the two methods of acquisition and laser vision is being considered. Artificial intelligence arbitrating various locations is also under consideration.
caption: Air-Cobot can estimate its position relative to an aircraft by using visual landmarks on the fuselage.[A 5]
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