Configuring the Deep Impact AutoNav System for Lunar, Comet and Mars Landing

Riedel, Joseph E.; Werner, Robert A.; Vaughan, Andrew T M; Mastrodemos, Nickolaos; Huntington, Geoffrey T.; Grasso, Christopher A.; Wang, Tseng-Chan; Myers, David M.; Gaskell, R. W.; Bayard, David S.

doi:10.2514/6.2008-6940

Cited by 16 publications

(12 citation statements)

References 5 publications

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“…The code, however, is now well over a decade old, and the limitations imposed by the inexpensive, rapid development, needed to be fixed for future uses. Over the past several years, this has been undertaken with the next generation AutoNav in prototype use 15 .This version builds on the experience gained from AutoNav's use in the missions described above, and incorporates many enhancements. The major ones are: (1) a new interface that is written in the Virtual Machine Language (VML), which allows for greater flexibility and ease of use, and (2) the addition of attitude guidance and control merged with the current translational navigation capabilities, and (3) the landmark tracking capability using a flight version of OBIRON.…”

Section: Future Mission Uses For Autonavmentioning

confidence: 99%

Autonomous Navigation for Deep Space Missions

Bhaskaran

2012

SpaceOps 2012 Conference

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Autonomous navigation (AutoNav) for deep space missions is a unique capability that was developed at JPL and used successfully for every camera-equipped comet encounter flown by NASA (Borrelly, Wild 2, Tempel 1, and Hartley 2), as well as an asteroid flyby (Annefrank). AutoNav is the first on-board software to perform autonomous interplanetary navigation (image processing, trajectory determination, maneuver computation), and the first and only system to date to autonomously track comet and asteroid nuclei as well as target and intercept a comet nucleus. In this paper, the functions used by AutoNav and how they were used in previous missions are described. Scenarios for future mission concepts which could benefit greatly from the AutoNav system are also provided.

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Section: Future Mission Uses For Autonavmentioning

confidence: 99%

Autonomous Navigation for Deep Space Missions

Bhaskaran

2012

SpaceOps 2012 Conference

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“…Autotracking of landmarks is discussed further in [10]. This is a complex combination of premission identi¦cation of landmarks and autonomous landmark identi¦cation and tracking.…”

Section: Introductionmentioning

confidence: 99%

Integrated communications and optical navigation system

Mueller

Pajer

Paluszek

2013

Progress in Flight Dynamics, Guidance, Navigation, Control, Fault Detection, and Avionics

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The Integrated Communications and Optical Navigation System (ICONS) is a §exible navigation system for spacecraft that does not require global positioning system (GPS) measurements. The navigation solution is computed using an Unscented Kalman Filter (UKF) that can accept any combination of range, range-rate, planet chord width, landmark, and angle measurements using any celestial object. Both absolute and relative orbit determination is supported. The UKF employs a full nonlinear dynamical model of the orbit including gravity models and disturbance models. The ICONS package also includes attitude determination algorithms using the UKF algorithm with the Inertial Measurement Unit (IMU). The IMU is used as the dynamical base for the attitude determination algorithms. This makes the sensor a more capable plug-in replacement for a star tracker, thus reducing the integration and test cost of adding this sensor to a spacecraft. Recent additions include an integrated optical communications system which adds communications, and integrated range and range rate measurement and timing. The paper includes test results from trajectories based on the NASA New Horizons spacecraft. NOMENCLATUREa planet radius or half distance between landmarks f focal length k 1 ¦rst-order optical distortion coe©cient in the imager focal plane k 2 second-order distortion coe©cient in the imager focal plane l i vector from the Sun to the planet center or the center of a straight line joining two landmarks o x image center x coordinate o y image center y coordinate p c the position in the camera frame p w the position in the world frame R transforms from the world to the camera frame

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“…RRDS develops new capabilities, while refining existing technology in order to lower risk and cost of implementation. Built atop an enhanced version of Virtual Machine Language [1], the flight-proven, award-winning [5] [6] sequencing software which sequenced the landing of Phoenix on Mars, RRDS also uses sequencing techniques developed for comet and asteroid touch-and-go sampling [7] [8] to provide sophisticated operational responses to conditions unique to deep space rendezvous and docking. These predecessor concepts are discussed below, followed by details of the RRDS implementation which built upon them.…”

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confidence: 99%

VML 3.0 Reactive Rendezvous and Docking Sequencer for Mars Sample Return

Grasso

2014

SpaceOps 2014 Conference

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Mars Sample Return poses some of the most challenging operational activities of any potential NASA deep space mission. Rendezvous of a vehicle with a sample canister in order to return the canister to Earth requires a variety of complex mathematical processing on a changing data set, coupled with the need to safely and effectively handle a large range of off-nominal conditions and spacecraft faults. Light speed delay isolates the spacecraft from real-time operator intervention, while inertial and situational uncertainties demand reactivity not required of typical spacecraft sequencing systems. These mission features call for a new class of sequencing capability: the Reactive Rendezvous and Docking Sequencer (RRDS). RRDS melds the rule-based reactivity needed for rendezvous and docking with sequence characteristics common to more traditional missions. Rules watch for conditions in order to react to the current situation, allowing a wide range of complex activities and safety-related responses to be concisely represented without complex procedural programming. RRDS state machines react to a variety potential conditions simultaneously. More traditional sequencing capabilities are present which provide multiple threads of executing logic, allow for timed activities, and deliver detailed insight into the operational system via traditional command and telemetry interfaces. The work for RRDS was successfully completed as a NASA phase II SBIR in 2013, under contract NNX11CB29C. VML 3.0 and the RRDS constructs which run atop it are currently available as commercial products from Blue Sun Enterprises. I. Mars Sample Return Missionars Sample Return [13] poses some of the most challenging operational activities of any potential NASA deep space mission. Rendezvous of a vehicle with a sample canister in order to return the canister to Earth requires a variety of complex mathematical processing on a changing data set, coupled with the need to safely and effectively handle a large range of offnominal conditions and spacecraft faults. Light speed delay isolates the spacecraft from real-time operator intervention during critical activities, while inertial and situational uncertainties demand reactivity not required of typical spacecraft sequencing systems. These mission features call for a new class of sequencing capability: the Reactive Rendezvous and Docking Sequencer (RRDS).

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Configuring the Deep Impact AutoNav System for Lunar, Comet and Mars Landing

Cited by 16 publications

References 5 publications

Autonomous Navigation for Deep Space Missions

Autonomous Navigation for Deep Space Missions

Integrated communications and optical navigation system

VML 3.0 Reactive Rendezvous and Docking Sequencer for Mars Sample Return

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