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Conference Papers Year : 2017

Vision-based navigation experiment onboard the removedebris mission


Airbus has been strongly involved in the design of Vision-Based Navigation (VBN) systems over the last years, with particular focus on applications such as planetary landing and orbital rendezvous. Based on this background and due to the increasing interest in Active Debris Removal (ADR), solutions for autonomous, vision-based navigation for non-cooperative rendezvous have been investigated. Dedicated image processing and navigation algorithms have been designed at Airbus and INRIA to meet this specific case, and some of them have already been tested over synthetic images and actual pictures of various spacecraft. As the next step, a VBN experiment will be conducted onboard the upcoming RemoveDebris ADR demonstration mission. The RemoveDEBRIS mission, sponsored by the European Commission FP7 programme, started in 2013 and will launch to the International Space Station late 2017 from where it will be deployed to a 400km orbit. In addition to the VBN experiment, the mission will perform other ADR experiments such as net and harpoon capture and dragsail de-orbiting. The VBN experiment will validate vision-based navigation equipment and algorithms, through ground-based processing of actual images acquired in flight of a debris mock-up target, in conditions fully representative of ADR. It will demonstrate state-of-the-art image processing and navigation algorithms based on actual flight data, acquired through three different but complementary sensors: two standard cameras, and a flash imaging LiDAR developed by CSEM, and validate a flash imaging LiDAR in flight.
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hal-01784234 , version 1 (03-05-2018)


  • HAL Id : hal-01784234 , version 1


Thomas Chabot, Keyvan Kanani, Alexandre Pollini, François Chaumette, Eric Marchand, et al.. Vision-based navigation experiment onboard the removedebris mission. GNC 2017 - 10th International ESA Conference on Guidance, Navigation & Control Systems, May 2017, Salzburg, Austria. pp.1-23. ⟨hal-01784234⟩
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