AI in Space Exploration Stephen Dabideen Yizenia Mora.

AI in Space ExplorationAI in Space Exploration

Stephen DabideenStephen Dabideen

Yizenia MoraYizenia Mora

AgendaAgenda

Planning and Scheduling (CASPER)Planning and Scheduling (CASPER)

Autonomous Navigation (AutoNav)Autonomous Navigation (AutoNav)

Communications with Earth (Beacon)Communications with Earth (Beacon)

Autonomous Onboard Science (ASE & OASIS)Autonomous Onboard Science (ASE & OASIS)

Data Mining (SKICAT)Data Mining (SKICAT)


What is AutoNav?What is AutoNav?Autonomous Optical Navigation system uses an expert-Autonomous Optical Navigation system uses an expert-system-like architecture to guide a spacecraft to its target, system-like architecture to guide a spacecraft to its target, first used in DS1first used in DS1

Enables a spacecraft to navigate independently of ground Enables a spacecraft to navigate independently of ground teams and ground linksteams and ground links

It commands the ion propulsion system and the spacecraft's It commands the ion propulsion system and the spacecraft's altitude control system to change trajectory as neededaltitude control system to change trajectory as needed

AutoNav also determines how much power to devote to the AutoNav also determines how much power to devote to the ion propulsion systemion propulsion system

Use location to determine how much energy generated by Use location to determine how much energy generated by solar arraysolar array

Intended to be reusableIntended to be reusable


Subsystems & functions:Subsystems & functions: Navigation executive functionNavigation executive function

Controls all AutoNav operations that cause physical action by Controls all AutoNav operations that cause physical action by spacecraft.spacecraft.

Optimizes time utilization by planning turn sequencesOptimizes time utilization by planning turn sequences Image processingImage processing

Integrates camera and imaging spectrometer to take pictures of Integrates camera and imaging spectrometer to take pictures of asteroids and stars, to determine its locationasteroids and stars, to determine its location

0.1 pixel accuracy0.1 pixel accuracy Orbit determinationOrbit determination

Uses a batch-sequential modified Kalman filter to compute the Uses a batch-sequential modified Kalman filter to compute the spacecraft’s positionspacecraft’s position

Maneuver planningManeuver planning Use OD to compute updates to upcoming trust plan.Use OD to compute updates to upcoming trust plan.


Spacecraft determines when ground support is Spacecraft determines when ground support is needed and what information is relevantneeded and what information is relevant

Advantages:Advantages: Reduces costs of the spacecraft-to-ground linkReduces costs of the spacecraft-to-ground link Downlinks only pertinent informationDownlinks only pertinent information


Two subsystemsTwo subsystems Subsystem 1:Subsystem 1:

End-to-end tone system to inform the ground whether data needs to be End-to-end tone system to inform the ground whether data needs to be sentsentOne of four possible requests (no action required, contact when One of four possible requests (no action required, contact when convenient, contact within a certain time, or contact immediately)convenient, contact within a certain time, or contact immediately)

Subsystem 2:Subsystem 2:Produce intelligent data summaries to be downlinked as telemetry when Produce intelligent data summaries to be downlinked as telemetry when ground responds to tone requestground responds to tone requestFour types of engineering telemetryFour types of engineering telemetry

High-level spacecraft information since the last ground contactHigh-level spacecraft information since the last ground contact Episode dataEpisode data Snapshot telemetrySnapshot telemetry Performance dataPerformance data

ELMER used to detect anomaliesELMER used to detect anomalies

Communications with Earth (Beacon)Communications with Earth (Beacon)Detecting Anomalies (ELMER)Detecting Anomalies (ELMER)

Traditional thresholdsTraditional thresholds Static, manually predefined red linesStatic, manually predefined red lines A lot of false alarmsA lot of false alarms

ELMER (Envelope Learning and Monitoring ELMER (Envelope Learning and Monitoring using Error Relaxation)using Error Relaxation) Time-varying alarm thresholdsTime-varying alarm thresholds Neural networksNeural networks Trained with nominal sensor dataTrained with nominal sensor data High- and low-expectation bounds (envelopes)High- and low-expectation bounds (envelopes)

Autonomous On-Board ScienceAutonomous On-Board Science

The dream:The dream: An autonomous Mars rover traversing the planets surface An autonomous Mars rover traversing the planets surface

for a couple of years, unattended by humans, collecting for a couple of years, unattended by humans, collecting and catching samplesand catching samples


The dream:The dream: An autonomous Mars rover traversing the planets surface An autonomous Mars rover traversing the planets surface

for a couple of years, unattended by humans, collecting for a couple of years, unattended by humans, collecting and catching samplesand catching samples

Reality check: Spirit and OpportunityReality check: Spirit and Opportunity 4 drivers per rover4 drivers per rover About 20 simulations per moveAbout 20 simulations per move Remote-controlled over 150 million miles awayRemote-controlled over 150 million miles away Opportunity's farthest distance to date: 15 mOpportunity's farthest distance to date: 15 m


Need for automated science:Need for automated science: Slim window of opportunity for discoverySlim window of opportunity for discovery Autonomy can provide more reactive, flexible architecture to Autonomy can provide more reactive, flexible architecture to

respond to unanticipated eventsrespond to unanticipated events Limited downlink bandwidthLimited downlink bandwidth Time delayTime delay

Accomplishments thus far:Accomplishments thus far: New method analyzing visible broadband images using neural New method analyzing visible broadband images using neural

networksnetworksImportant features extracted and combined with spectral Important features extracted and combined with spectral classifications and decisions are made using a decision tree classifications and decisions are made using a decision tree directed towards specific goalsdirected towards specific goals

Analysis of spectral dataAnalysis of spectral dataHierarchy of neural nets place spectra into progressively more Hierarchy of neural nets place spectra into progressively more detailed geologic classesdetailed geologic classesDecompose mixtures from unknown spectraDecompose mixtures from unknown spectraWill help automate characterization of planetary surfaceWill help automate characterization of planetary surface

Autonomous On-Board Science (ASE)Autonomous On-Board Science (ASE)

The Autonomous Sciencecraft Experiment (ASE)The Autonomous Sciencecraft Experiment (ASE) Used on Earth Observing One (EO -1)Used on Earth Observing One (EO -1) Demonstrates integrated autonomous scienceDemonstrates integrated autonomous science Features several science algorithms including:Features several science algorithms including:

Event detectionEvent detection Feature detectionFeature detection Change detectionChange detection

Analyzes to detect trigger conditions such as science eventsAnalyzes to detect trigger conditions such as science events Based on these observations CASPER will replanBased on these observations CASPER will replan Science analysis techniques include:Science analysis techniques include:

Thermal anomaly detectionThermal anomaly detection Cloud detectionCloud detection Flood scene classificationFlood scene classification

Autonomous On-Board Science (OASIS)Autonomous On-Board Science (OASIS)

Onboard Autonomous Science investigation SystemOnboard Autonomous Science investigation System Due to limited bandwidth, rovers must “intelligently” select what data to Due to limited bandwidth, rovers must “intelligently” select what data to

transmit back to Earthtransmit back to Earth How?How?

Machine leaning techniques to prioritize dataMachine leaning techniques to prioritize data

The capability of OASIS enables a rover to perform data collections The capability of OASIS enables a rover to perform data collections which were not originally planned, even without having to wait for a which were not originally planned, even without having to wait for a command from Earthcommand from Earth

Researchers are interested in:Researchers are interested in: Pre-specified signals of scientific interestPre-specified signals of scientific interest Unexpected or anomalous featuresUnexpected or anomalous features Typical characteristics of a regionTypical characteristics of a region

OASIS has different levels of autonomy, from following a predefined OASIS has different levels of autonomy, from following a predefined path and taking only planned measurements to commanding the rover path and taking only planned measurements to commanding the rover to deviate slightly from path to get new measurementsto deviate slightly from path to get new measurements


What?What? SKy-Image Cataloging and Analysis ToolSKy-Image Cataloging and Analysis Tool Assign galaxies and stars to known classes and identify new Assign galaxies and stars to known classes and identify new

classesclasses

Why?Why? Databases are too large for an astronomer to analyze manuallyDatabases are too large for an astronomer to analyze manually

How?How? Automated Bayesian classificationAutomated Bayesian classification Attributes such as brightness, area, color, morphology, …Attributes such as brightness, area, color, morphology, … Training data consisting of astronomer-classified sky objectsTraining data consisting of astronomer-classified sky objects Classifiers applied to new survey imagesClassifiers applied to new survey images


Results:Results: One of the most outstanding successesOne of the most outstanding successes 1,000-10,000 times faster than astronomers1,000-10,000 times faster than astronomers More consistent classificationMore consistent classification Able to classify extremely faint objectsAble to classify extremely faint objects Astronomers freed for more challenging analysis and Astronomers freed for more challenging analysis and

interpretationinterpretation Comprehensive catalog of approximately 3 billion Comprehensive catalog of approximately 3 billion

entriesentries

AI in Space Exploration Stephen Dabideen Yizenia Mora.

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