The fully programmable spacecraft: procedural sequencing for JPL deep space missions using VML (Virtual Machine Language)

Grasso, Christopher A.

doi:10.1109/aero.2002.1036829

Cited by 18 publications

(9 citation statements)

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“…Onboard commanding and resource management b. Automated response to faults/opportunities based on constraints and resources c. Examples: CASPER (Chien, Knight, Stechert, Sherwood, and Rabideau, 1999), Remote Agent Experiment (RAX) (Bernard et al, 1998;Muscettola, Nayak, Pell, and Williams, 1998), RHex (Saranli, Buehler, and Koditschek, 2001) and CREST (Woods et al, 2008) (Grasso, 2002), Spacecraft Command Language (SCL) (Buckley and Vangaasbeck, 1994), Titan (Williams, Ingham, Chung, and Elliott, 2003), etc.…”

Section: Capabilities-enabling Active Resiliencementioning

confidence: 99%

Engineering Resilient Space Systems

Day¹,

Ingham²,

Murray³

et al. 2015

INSIGHT

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Several distinct trends will influence space exploration missions in the next decade. Destinations are becoming more remote and mysterious, science questions more sophisticated, and, as mission experience accumulates, the most accessible targets are visited, advancing the knowledge frontier to more difficult, harsh, and inaccessible environments. This leads to new challenges including: hazardous conditions that limit mission lifetime, such as high radiation levels surrounding interesting destinations like Europa or toxic atmospheres of planetary bodies like Venus; unconstrained environments with navigation hazards, such as free-floating active small bodies; multielement missions required to answer more sophisticated questions, such as Mars Sample Return (MSR); and long-range missions, such as Kuiper belt exploration, that must survive equipment failures over the span of decades. These missions will need to be successful without a priori knowledge of the most efficient data collection techniques for optimum science return. Science objectives will have to be revised 'on the fly', with new data collection and navigation decisions on short timescales. Yet, even as science objectives are becoming more ambitious, several critical resources remain unchanged. Since physics imposes insurmountable light-time delays, anticipated improvements to the Deep Space Network (DSN) will only marginally improve the bandwidth and communications cadence to remote spacecraft. Fiscal resources are increasingly limited, resulting in fewer flagship missions, smaller spacecraft, and less subsystem redundancy. As missions visit more distant and formidable locations, the job of the operations team becomes more challenging, seemingly inconsistent with the trend of shrinking mission budgets for operations support. How can we continue to explore challenging new locations without increasing risk or system complexity? These challenges are present, to some degree, for the entire Decadal Survey mission portfolio, as documented in Vision and Voyages for Planetary Science in the

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Section: Capabilities-enabling Active Resiliencementioning

confidence: 99%

Engineering Resilient Space Systems

Day¹,

Ingham²,

Murray³

et al. 2015

INSIGHT

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“…Many of the state and transition concepts behind RRDS originated with the highly successful 2009 entry, descent, and landing (EDL) of the Phoenix spacecraft on Mars, in turn having roots in other missions [2][3], including Spitzer [4]. State concepts proved so stable and successful that the mainline landing sequence worked the first time, and landed the vehicle in every test where external simulator components were working correctly.…”

Section: A Phoenix Entry Descent and Landingmentioning

confidence: 99%

“…Five versions have been implemented so far. VML has been used or is in use on fifteen NASA flight missions to date, including Stardust [2], Genesis, Mars Odyssey, Spitzer Space Telescope [3][4] [8], MRO, Dawn, Phoenix, JUNO, GRAIL, MAVEN, OSIRIS-REx, InSIGHT, and the RESOLVE lunar regolith analysis mission. A timeline of software use appears in Figure 5.…”

Section: Virtual Machine Languagementioning

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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“…The Jet Propulsion Laboratory (JPL) owns all rights to VML and is available royalty-free for use on any NASA funded mission. Sequences developed in VML are procedural in nature [2]. At any particular time, only one instruction is active on a sequence engine.…”

Section: Vml Overviewmentioning

confidence: 99%

Spitzer Space Telescope Use of the Virtual Machine Language

Peer

Grasso

2005

2005 IEEE Aerospace Conference

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Spitzer Space Telescope makes the most extensive use of the Virtual Machine Language (VML) sequencing language of any mission launched to date. The use of VML has presented minor ground integration challenges to the mission and provides many benefits. While other missions such as Cassini use sequencing languages that can provide similar capabilities, VML's syntax, tools, and approach provide greater functionality in practice.Benefits of the sequencing approach taken include reduction in uplink volume, increased science efficiency, simplified operations, and increased mission safety. VML provides more commonality between missions than previous sequencing approaches, in an environment more like high level programming. It would be difficult to determine the life-cycle cost impact of using VML on Spitzer, but Spitzer's investment in the technology should enable future missions to achieve cost savings while simultaneously increasing autonomation and safety. 1,2

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The fully programmable spacecraft: procedural sequencing for JPL deep space missions using VML (Virtual Machine Language)

Cited by 18 publications

References 0 publications

Engineering Resilient Space Systems

Engineering Resilient Space Systems

VML 3.0 Reactive Rendezvous and Docking Sequencer for Mars Sample Return

Spitzer Space Telescope Use of the Virtual Machine Language

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