Mission Independent Group Feb. 4 th 2009 Planning Concept Meeting.

Mission Independent Group Feb. 4th 2009

Planning Concept Meeting

Planning Concept Workshop (2)

Agenda - morning

Presentations: conceptual level, implementation not discussed

9:30 Rosetta

10:00 BepiColombo

10:30 break

10:45 MIG: Generic planning concept + lessons learned from routine operations

11:15 GSP activity

11:30 TEC-SWM: Conceptual SGS proposal

12:15 Lunch


Agenda – early afternoon

Discussion sessions

13:00 'science driven' observation selection

assessing the science objectives - are they achievable – attach value?

capturing the planning information - what is needed to identify and prioritise

observations?

defining use cases - appropriate levels of abstraction for effective planning

observation life cycle - mission analysis, opportunity analysis through to ingestion in

the archive

14:00 'knowledge driven' planning process

defining planning horizons based on planning information availability/predictability

preservation of planning information over planning boundaries


Agenda – late afternoon

15:00 'prediction limited' plan validation

plan validation reference

modelling/simulation needed for resource assessment (pointing, power, thermal, data)

SPICE for planning?

16:00 Identifying requirements - first steps

prerequisites for ROS, BC based on mission characteristics

feasibility assessment (P v/d Plas)

consolidating requirements with other groups

17:00 next steps

outline meeting plan

involvement of other missions/groups

prototyping and studies

responsibilities


Generic Planning Concept


Present Status

A science planning concept does not exist for the planetary missions in routine phase Planning requirements are poorly documented.

All SGS for planetary missions in routine phase have tools for: Simulation and request validation (MAPPS, EPS, MIRA) Visualisation of underlying request files (MAPPS, MIRA)

There are no science planning tools in use, done by the teams PI teams prepare requests without access to all available planning information

and/or planning tools. Selections made without assessment of impact on other participants Any choices made do not propagate to all parties Result: conflicting requests, unnecessary iteration, sub-optimal planning

Planning process is not transparent Information lost whenever requests cross an interface The goals of the science planning are obscured Prioritisation of observations extremely hard (impossible ?) to assess

No feedback from previous plans, no knowledge of future opportunities Observations selection not driven by the LTP science goals


Need for a Planning Concept

All missions face the same science planning problem: How can the science return be optimised while remaining within the operational constraints of the mission?

The planning process should be transparent and place all planning selections in the context of the entire mission (as a minimum).

Generic Concept: Formulate the science goals in operational terms Identify the conditions to satisfy an experiment teams’ request Find the best time in the mission to schedule the requests Prioritise requests to optimise the science return of the mission Ensure that the operational constraints are not violated

Generic Concept: Formulate the science goals in operational terms Identify the conditions to satisfy an experiment teams’ request Find the best time in the mission to schedule the requests Prioritise requests to optimise the science return of the mission Ensure that the operational constraints are not violated

Generic Concept: Identify the data flow between all involved planning parties Propagate planning choices Track the progress of plans

Generic Concept: Identify the data flow between all involved planning parties Propagate planning choices Track the progress of plans


Goal of Science Planning

Science goals of ESA missions have remained top—level, vague, ambitions

well specified constraintspermit a plan to be validated

well specified constraintspermit a plan to be validated

resources need to be known,calculated or predicted.

resources need to be known,calculated or predicted.

science return must be quantifiable

science return must be quantifiable

Maximise the science return without violating constraints

or exceeding resources

Maximise the science return without violating constraints

or exceeding resources

Generic Concept: Identify achievable science objectives for the nominal mission

Generic Concept: Identify achievable science objectives for the nominal mission


Science Driven Analysis

Opportunity analysis: sufficient planning information being available to reliably identify when observations are possible

Planning information can be categorised as: static – unchanging characteristics of a mission predictable – information that can be modelled or simulated unpredictable – uncertainty needs to be accommodated within the plan

Generic Concept: Only the SGS has access to the information needed to identify opportunities To accomplish this it is necessary to know:

when a predetermined set of information is complete with acceptable accuracy how to proceed to obtain the opportunities

Generic Concept: Only the SGS has access to the information needed to identify opportunities To accomplish this it is necessary to know:

when a predetermined set of information is complete with acceptable accuracy how to proceed to obtain the opportunities


Static planning information

The concept will need accommodate some parameters of the planning problem that have already been fixed:

platform has been designed payloads have been selected

Able to define how experiments observe and what the target allows us to observe

Generic Concept:

Fixed aspects of the mission can be treated as planning information

Detector characteristics, sensitivity criteriaPlatform limitationsThe target object (known to varying degrees, from Smart-1 to Rosetta)

Generic Concept:

Fixed aspects of the mission can be treated as planning information

Detector characteristics, sensitivity criteriaPlatform limitationsThe target object (known to varying degrees, from Smart-1 to Rosetta)


Observation requirements

E.g. For a detector to perform an certain observation requires:

Generic Concept: the characteristics of a mission represent the known/static planning information they can form the foundation of a valid science observation

Generic Concept: the characteristics of a mission represent the known/static planning information they can form the foundation of a valid science observation

Observation requirement Known information

a phase angle between … and ... degrees Detector sensitivity

to be orbit aligned with FoV … Detector design

an altitude of less than ... km Resolving power

a footprint velocity of less than ... m/s Minimum integration time

Solar longitude between ... and ... degrees Target seasons

10% overlap with adjacent observation Coverage requirements


Unknown planning information

The orbit may be undefined it will be constrained by the experiment design: maximum footprint velocity (minimum dwell time)

Coverage requirements are well known: Spatial/spectral/temporal coverage Target environment

The orbit is further constrained further by the spacecraft design: spacecraft fuel budget slew rates (AOCS) spacecraft resources (data budget, power budget)

Generic Concept: SGS should have the means to select a baseline orbit that will optimise the science return within the resources.

Generic Concept: SGS should have the means to select a baseline orbit that will optimise the science return within the resources.


Predictable Information

In terms of a planning concept it is only important to: identify the missing information needed to validate a plan demonstrate that it will be predictable and at what time (e.g. once a

baseline orbit is delivered).

MEX approach to opportunity analysis enhances the information associated to a valid opportunity: Primary geometric parameters used to identify a valid opportunity contextual geometry used to provide a qualitative assessment

Generic Concept:

Planning horizons are based on planning information availability/predictability

Generic Concept:

Planning horizons are based on planning information availability/predictability


Knowledge driven planning

Planning Horizon Description Required Information Outcome

Mission analysis all possible observationsgiven the known andpredictable missioncharacteristics

Orbit candidates Achievable scienceobjectives

Science activity plan Assessment of thecontribution to definedscience objectives

Science objectivesAssessment criteria

Mission PhasesPrioritisation

Long-term schedule initial selection based ona prioritisation ofobservations to resolve anachievable plan.

Orbit predictionResource estimationsFeedback from executedobservations

Baseline schedule

Medium term schedule a refinement of the selection based on the latest resourceassessment

Baseline scheduleAccurate orbit predictionAccurate resource

prediction

Observation selection

Short-term schedule A refinement to theobservation parameters

Previous observation resultsPredicted attitude

Commanded observations

Feedback Results from a plannedObservation campaign

Planned observationsStatus of each observation

Re-prioritise future obs.Refresh from LTP down


Science Driven Planning revisited

Observations

Measurements

ScienceObjectives

“Scenarios”

Orbit types

Operationalconstraints

Science Themes& Sub-Themes

Trajectory

ScienceOperations

Top-level science goals

Quantifiable

Physical parameters

Environment

Timeline Pointing

Sequences PTR blocks

ITL/POR PTRIteration on operational missions

Iteration based on all available planning information

Link between operations and pointing lost

Link to observation lost


Planning iteration

For science driven planning the iteration must be on observation level Avoid the loss of planning information Permits higher level abstraction Commanding requests can be generated

Generic Concept: Planning information should be preserved over planning horizons and interfaces. Iterations should take place on object that pools all of the information related to an observation

Generic Concept: Planning information should be preserved over planning horizons and interfaces. Iterations should take place on object that pools all of the information related to an observation


Resource Assessment

For each of the resource types: There will be a reference model The nature of the mission will demand a level of accuracy for each

resource type

Generic Concept:

SGS validation must be synchronised with the reference model Resource estimation will be used to assess validity of observation

Accuracy of prediction may impact the science return depending on the mission characteristics

Critical resources should be identified Acceptable level of accuracy for each resource type

Generic Concept:

SGS validation must be synchronised with the reference model Resource estimation will be used to assess validity of observation

Accuracy of prediction may impact the science return depending on the mission characteristics

Critical resources should be identified Acceptable level of accuracy for each resource type


GSP Planning Information Repository

Simulation Modules

Environment

Payload

Spacecraft

Thermal

Slew Module

Science Opportunity Analyser

Planner & Scheduler

RequestGeneration

Visualisation Module

Requests

Geometry

Existing

Prototype

Missing

InformationRepository

Payload DefinitionObservation RequestScience ObjectivesConstraintsPrioritiesFeedbackExecution SuccessData Quality

Focus of study:Information repository

Reuse existing /prototype modules


Requirements


Drivers


Capabilities


Repository Architecture


Development Schedule

Prerequisite: Generic planning concept Reference SGS implementation

Mission Independent Group Feb. 4 th 2009 Planning Concept Meeting.

Documents

Transcript of Mission Independent Group Feb. 4 th 2009 Planning Concept Meeting.