{"project":{"acronym":"","projectId":93251,"title":"Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations","primaryTaxonomyNodes":[{"taxonomyNodeId":10974,"taxonomyRootId":8816,"parentNodeId":10973,"level":3,"code":"TX17.2.1","title":"Onboard Navigation Algorithms","definition":"This area covers algorithms (and their associated flight software) for autonomous onboard estimation of flight path/orbit/trajectory parameters and associated uncertainties from navigation sensor measurements.","exampleTechnologies":"Algorithms for optical navigation, terrain relative navigation, autonomous rendezvous and docking, autonomous hazard detection and avoidance, autonomous space-based navigation (optical or Global Positioning System (GPS) Cislunar), X-ray navigation, Simultaneous Localization and Mapping (SLAM), light detection and ranging (LIDAR)-based navigation, inertial navigation (translation) filter, inertial attitude estimation filter, ascent vehicle filter, Earth-independent deep space navigation, celestial navigation, landmark navigation, X-ray pulsar navigation, vehicle-relative navigation (translation) filter, vehicle-relative attitude filter, swarm navigation, angles-only navigation, double line of sight navigation, small body prox ops and landing filter","hasChildren":false,"hasInteriorContent":true}],"startTrl":1,"currentTrl":1,"endTrl":3,"benefits":"
Autonomous relative navigation and pose estimation enables a number of missions of interest to NASA including satellite inspection and servicing, rendezvous and docking, and small body (asteroid and comet) exploration. Due to its enhanced ability to estimate in the presence of noisy measurements and clutter, SLAM has the potential to significantly improve our ability to perform relative navigation and pose estimation with an asteroid or satellite that is not well known beforehand, operate in a wider range of lighting conditions or in a lower signal-to-noise environment.
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