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Liounis, Andrew

Publications and source records attributed to Liounis, Andrew.

9 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Building Lunar Maps for Terrain Relative Navigation and Hazard Detection Applications

Terrain Relative Navigation (TRN) systems that localize a spacecraft with respect to a map of the surface by comparing descent imagery to that reference map can only be as accurate as the reference map itself. Accurate map products that are based on orbital reconnaissance data must be validated for navigation applications to ensure that all relevant error sources are minimized. Currently available map products have been generated for scientific applications, so the need for accurate TRN maps remains a gap to be filled for upcoming lunar lander missions, in particular missions to the South Pole region. Additionally, representative high-resolution maps that contain lander-scale features are needed for successful development and testing of Hazard Detection (HD) systems. This paper describes one of NASA’s current efforts to develop benchmark data sets that can be used for developing and testing TRN and HD algorithms as well as suggested processes and metrics for generating and validating lunar maps that can be used for navigation and hazard detection.

Beyer, Ross A.↗
NASA NTRS2020

Osiris-Rex Shape Model Performance During the Navigation Campaign

The Navigation Campaign of the OSIRIS-REx mission began when the first image of Bennu was recorded by the PolyCam high-resolution imager on Au-gust 17, 2018. In the ensuing months, two teams began building shape models based on imagery taken during the Approach and Preliminary survey phases to be used for the transition to landmark navigation in the Orbital A phase. The orbit determination team began analyzing and characterizing the performance and errors associated with each shape model delivery working closely to iterate on the next shape model delivery. By the end of Orbital A, shape models produced by the Altimetry Working Group and JPL exceeded pre-launch performance re-quirements. This paper provides a summary of the analysis performed during operations.

Leonard, Jason M.↗
NASA NTRS2019

Independent Optical Navigation Processing for the Osiris-Rex Mission Using the Goddard Image Analysis and Navigation Tool

The OSIRIS-REx mission to the asteroid(101955) Bennu heavily relies on optical navigation to provide relative state information between the asteroid and the spacecraft. These measurements enable determination of the spacecraft's orbit to the tight requirements needed to meet the science goals of the mission. In this document we describe the algorithms and techniques used by the Goddard independent verification and validation navigation effort to extract these measurements from the images taken by the spacecraft during the mission.We also demonstrate the capabilities of the techniques by showing the high accuracy of the results when used in an orbit determination solution.

Liounis, Andrew↗
NASA NTRS2019

A Novel Surface Feature Navigation Algorithm Using Ray Tracing

We demonstrate a novel single-bounce ray tracing approach to landmark identification for surface feature-based relative navigation. A priori knowledge of the camera pose and known topographic maps for each landmark are used to render the potentially visible landmarks via ray tracing into the image frame. These templates are registered with a search region around the predicted location for each landmark in the image, to locate its observed center. This procedure is applied to images from the OSIRIS-REx Orbital A and Orbital B mission phases, and the results are compared with those obtained via previous landmark identification methods.

Gnam, Chris↗
NASA NTRS2016

Performance Characterization of a Landmark Measurement System for ARRM Terrain Relative Navigation

This paper describes the landmark measurement system being developed for terrain relative navigation on NASAs Asteroid Redirect Robotic Mission (ARRM),and the results of a performance characterization study given realistic navigational and model errors. The system is called Retina, and is derived from the stereophotoclinometry methods widely used on other small-body missions. The system is simulated using synthetic imagery of the asteroid surface and discussion is given on various algorithmic design choices. Unlike other missions, ARRMs Retina is the first planned autonomous use of these methods during the close-proximity and descent phase of the mission.

Navigation↗
NASA NTRS2016

Relative Terrain Imaging Navigation (RETINA) Tool for the Asteroid Redirect Robotic Mission (ARRM)

As a part of the NASA initiative to collect a boulder off of an asteroid and return it to Lunar orbit, the Satellite Servicing Capabilities Office (SSCO) and NASA GSFC are developing an on-board relative terrain imaging navigation algorithm for the Asteroid Redirect Robotic Mission (ARRM). After performing several flybys and dry runs to verify and refine the shape, spin, and gravity models and obtain centimeter level imagery, the spacecraft will descend to the surface of the asteroid to capture a boulder and return it to Lunar Orbit. The algorithm implements Stereophotoclinometry methods to register landmarks with images taken onboard the spacecraft, and use these measurements to estimate the position and orientation of the spacecraft with respect to the asteroid. This paper will present an overview of the ARRM GN&C system and concept of operations as well as a description of the algorithm and its implementation. These techniques will be demonstrated for the descent to the surface of the proposed asteroid of interest, 2008 EV5, and preliminary results will be shown.

Navigation↗