Innovative Technologies in support of Mission Operations:Experiences and Perspectives

Alessandro DonatiAdvanced Mission Concepts and Technologies Office

OPS-HSC

OPS-G Forum ESOC, 2.2.2007

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Outline• Introduction

• The Motivation– Future missions and future needs in operations

• The Approach– Suitable working methods

• The Present– Overview of recent activities and achievements

• The Future– Planned projects for the near future

• Conclusion

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• Introduction

• The Motivation– Future missions and future needs in operations

• The Approach– Suitable working methods

• The Present– Overview of recent activities and achievements

• The Future– Planned projects for the near future

• Conclusion

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Term of Reference & Objectives

• Map innovative operations concepts and associated functions & performance with enabling new technologies

• Promote the application of new technologies for ESA core business in spacecraft and ground segment operations

• Getting ready for future Missions with efficient, effective and proven operations technologies

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• Introduction

• The Motivation– Future missions and future needs in operations

• The Approach– Suitable working methods

• The Present– Overview of recent activities and achievements

• The Future– Planned projects for the near future

• Conclusion

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Looking at the future

• Challenging missions– Space Exploration, Rovers, Lunar Base– Formation Flying– Coordinated Earth Sensing

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Looking at the future• Challenging Requirements :

– Onboard autonomous (re)Planning– Onboard Diagnosis & Repair Capability– Onboard autonomous target detection– Onboard Payload Products Management– Radiation Hazard Management & Mitigation– Optimal & Adaptable Resource Management– Advanced monitoring and Decision Support– Multimission Operations Automation & Supervision– Specialists Training & Certification– Launch-delay-tolerant Service Provision– ……………

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• Introduction

• The Motivation– Future missions and future needs in operations

• The Approach– Suitable working methods

• The Present– Overview of recent activities and achievements

• The Future– Planned projects for the near future

• Conclusion

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Projects Characteristics

• Practical studies on future mission’s technology infusion for advanced operational concepts– Operations concepts & technology assessment– Internal feasibility study– Prototype implementation – Extended operational validation as “shadow”

application• Comparison / competition of different

approaches and technologies

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Suitable working methods

• From long-term goal derive step-by-step pattern and validate it !– Automation on ground– Autonomy on ground– On-board automation– On-board autonomy

• Operational Environment– Mission Independent Ontology Definition

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Suitable working methods• Spiral iterative prototyping

– Requirements & Priorities updated at each iteration– Frequent deliveries based on time, not on content

• Extreme programming– Users part of the development team– Streamlined involvement of the user representative– Pair programming– ……………

t

DeliveryDeadlineeffort

traditional

pair programming

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Project Workflow

Real Project Case

Real Project Case

Prototype Implementation

Prototype Implementation

ProvenSolutionProvenSolution

Operational Validation

Operational Validation

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Project Workflow

Real Project Case

Real Project Case

TechnologiesTechnologies

Prototype Implementation

Prototype Implementation

Flight/Ground Control TeamsProject Teams

Future MissionsStudy Teams

Operational Validation

Operational Validation

R&D Spin-inUniversities

Industry

ConferencesSeminars

ProvenSolutionProvenSolution

In-houseLectures,Training

Infrastructure/ Family Missions

Lessons learnt/Feedbackfrom Users/Developers

Lessons learnt/Feedbackfrom Users/Developers

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Some lessons learnt for successful technology infusion

• Have a common data gathering interface– MUST allows (remote) multi-mission data acquisition– APSI will be the P&S experimental platform

• Listen for needs & avoid forced technology push– Operations community requires new operation concept– Iterative design process with users involvement– Show results and improvements

• Plan for an extended validation campaign– Continuous support is required for fine-tuning– Critical phase for accepting the “new”

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• Introduction

• The Motivation– Future missions and future needs in operations

• The Approach– Suitable working methods

• The Present– Overview of recent activities and achievements

• The Future– Planned projects for the near future

• Conclusion

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Gyro Diagnostic Tool

• ENVISAT Gyro performance evaluation & diagnostic

• Based on fuzzy logic diagnostic engine & past operational experience

• Allows early identification of anomalous behaviour

• From corrective/ preventive to predictive maintenance

IDVA outputs

RandomNoise

RandomDrift

Gyro Mode

Raw inputs (from TM data)Note: Different time windows

Pre-processing

De-fuzzificationFuzzificat ion Inference

Engine

Gyroscope alarm level

• Transform the fuzzy outputs of the model into a crisp alarm level

• Using the fault-detection model (expressed in a set of rules), infer the diagnostic

• Transform crisp inputs into fuzzy sets using membership functions

• Transform raw data into derived variables for diagnostic process• Estimate time series

Gyroscope alarm level

• Transform the fuzzy outputs of the model into a crisp alarm level

• Using the fault-detection model (expressed in a set of rules), infer the diagnostic

• Transform crisp inputs into fuzzy sets using membership functions

• Transform raw data into derived variables for diagnostic process• Estimate time series

Knowledge base

Supporting ENVISAT

as of Dec. 2002

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Mission Utility & Support Tools

• Platform and gateway for introducing innovative technologies in operations

• Client applications include:– S/C Performance

evaluation – Radiation monitoring– Behavioural modelling– Remote monitoring,

alarming and diagnosis– Augmented reality S/C

status awareness• Currently supporting 7

missions• MUST server in EDDS

First deployment Dec. 2003

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MEXAR 2

• Mars Express science & housekeeping data dumping scheduling

• Based on Constraint Satisfaction Programming

• Allows automatic conflict free scheduling scenario generation & optimisation

• 50% reduction for daily dump plan preparation & increased science return

• RAXEM for TC uplink scheduling under prototyping Supporting

Mars Express as of Oct. 2005

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Space Environment Information System for OPerations

• Space weather events monitoring and spacecraft effects mitigation

• Based on data warehousing and data mining techniques

• Allows alarming and forecasting of space weather hazards (radiation belt crossing, CME protons interception)

• Research institutes can make use of SEISOP for test-bedding their space weather dynamic models

• Operational implementation of SEISOP on its way.

Supporting Integral

as of Sept. 2005

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Other Investigations

• Virtual Sensor (Artificial Neural Network)• Fault Analysis (Data Mining)• Reaction Wheels Bias Manoeuvre Fuel Consumption

Optimisation (Genetic Algorithm)

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• Introduction

• The Motivation– Future missions and future needs in operations

• The Approach– Suitable working methods

• The Present– Overview of recent activities and achievements

• The Future– Planned projects for the near future

• Conclusion

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System Level Activities• GSP’s study on Advanced Mission Operations Concepts &

Technologies for Future ESA Missions– Mission operations concepts assessment – Roadmap for associated enabling technology for operations– Joint OPS-HSC & OPS-HSA activity

• Definition of common Mission Ontology

• Reinforce cooperation and synergy within ESA, with NoCs and other agencies (e.g. NASA JPL)

• Spin-on: Acquisition of industrial experience on exploiting technology for similar applications in other domains

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Advanced Planning and Scheduling Initiative

• APSI: Plug-in Experimental Platform for Forging and Validating P&S A.I. modules

• Multi-user & Multi-mission• Case Studies selection under way• Coordinated with OPS-G MPS Framework activity

• Expected quantitatively and qualitatively “better”plans

• Reuse of A.I. functional modules in operational MPS Framework

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Automation of “Clerical” Tasks

• Automatic Report Generators– SEISOP, CERTAIN, REST

• Digital Logging System– Multi-mission environment, web-based services

• End-to-end Communication Link Supervision– Quality of service monitoring– Failure detection and diagnosis

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Power Consumption of Thermal s/sModelling

• Request: forecast the expected power consumption of Mars Express thermal s/s

• Approach:– Based on past orbits observation through Telemetry and

ancillary data– Use of Data Mining techniques– Parallel investigation of two Universities + internal

• Expected increase of payload activity through relaxation of power allocation margins

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Operations Anomaly Investigation and Root Cause Analysis

• Request: identify and validate a technique to automatically classify recorded anomalies– Root cause identification

• Approach:– Case Base Reasoning technique– Complexity increased step by step– Clustering of “similar” anomalies

• Automation of anomaly processing• Automated anomaly classification• Decision support system for anomaly resolution

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Rover Operations

• Installation of remote Rover M&C system at ESOC– Acquisition of rover operations expertise– Operational feedback to ESTEC Robotic section

• Investigation on technology for autonomy concept– Support prototyping of remote agents for

planning, execution and repair

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ATV RV & Docking Scheduler

• Decision Support Tool for:– RV & Docking Scenarios generation– Docking opportunities evaluation– Nominal RV&D timeline generation– Back-up RV&D opportunities selection

• Based on Constraint Programming (A.I.)

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Near Future Missions & Challenges

• Increased level of automation and autonomy

• Risk assessment and risk mitigation• Increased expectations in science return• Optimisation in resources exploitation

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Technology Infusion in Operations & Challenges

• Validation and Robustness of Implemented Solutions– Use of “shadow” system for extended operational validation,

before use– Testing policy

• Transfer of functionalities from ground to space– Synergy between spacecraft engineering & operations

communities (D/TEC, D/OPS)– Gradual steps from ground to space segment, including on-

ground validated automation and autonomy concepts– On-board “standard” SW platform

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Vision for the future…

• Make use of node-based architecture– Satellite(s), Rover(s) and Mission Control(s) are

considered functional nodes– Functions are transferred btw. nodes as needed

• mission phases, • contingencies, • information availability, goals…

– Enabled by agent technology

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Vision for the future…

• Plan for A.I. Technology Demonstration Mission– To validate advanced operations concepts

• Autonomous planning & scheduling• Autonomous exec monitoring & diagnosis• Supervision based operations

– To facilitate A.I. infusion in support of mission operations tasks

• Increase Inter-Agencies Synergy– on A.I. prototyping and exploitation experiences

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Conclusion• Infusion of technology is beneficial for

mission operations• Future missions will require further level of

automation and autonomy• For mitigating risks a step-by-step validation

process is required• Mission Operations requires additional

funding from ESA R&D programmes

Innovative Technologies in support of Mission Operations:Experiences and Perspectives

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Thank you for your attention !

Time for questions…

Technology Infusion forMission Operations

of Future Missions Validated on Current Flying Missions