robotic space explorers: to boldly go where no ai system has gone before

Robotic Space Explorers:To Boldly Go Where No AI System

Has Gone Before

A Story of Survival

16.412J/6.834J

September 19, 2001

Copyright B. Williams 16.412J/6.834J, Fall 01

Readings and Assignment

Model-based Agents:• Remote Agent: to Boldy

Go Where No AI System Has Gone Before,N.Muscettola, P. Nayak, B. Pell and B. Williams, Artificial Intelligence 103 (1998) 5-47.

Partial Order Planning (for next lecture)• AIMA Chapter 11, Chapter 10, section on unification algorithm.

For Problem Set 3:• Path Planning Using Lazy PRM,

R. Bohlin and L. Kavraki, ICRA 2000.


Outline

• Motivation

• Model-based autonomous systems

• Remote Agent Example

Cassini Maps Titan courtesy JPL

• 7 year cruise

• ~ 150 - 300 ground operators

•~ 1 billion $

• 7 years to build

A Capable Robotic Explorer: Cassini

•150 million $

•2 year build

• 0 ground ops

Faster, Better, Cheaper

courtesy JPL

``Our vision in NASA is to open the Space Frontier . . . We must establish a virtual presence, in space, on planets, in aircraft and spacecraft.’’

- Daniel S. Goldin, NASA Administrator, May 29, 1996


Four launches in 7 months

Mars Climate Orbiter: 12/11/98Mars Polar Lander: 1/3/99

Stardust: 2/7/99 QuickSCAT: 6/19/98courtesy of JPL


Miscommanded:• Mars Climate Orbiter• Clementine

courtesy of JPL

Spacecraft should be embodied with a survival instinct


Vanished:• Mars Polar Lander• Mars Observer

courtesy of JPL

Spacecraft require commonsense…


Traditional spacecraft commanding

GS,SITURN,490UA,BOTH,96-355/03:42:00.000; CMD,7GYON, 490UA412A4A,BOTH, 96-355/03:47:00:000, ON; CMD,7MODE, 490UA412A4B,BOTH, 96-355/03:47:02:000, INT; CMD,6SVPM, 490UA412A6A,BOTH, 96-355/03:48:30:000, 2; CMD,7ALRT, 490UA412A4C,BOTH, 96-355/03:50:32:000, 6; CMD,7SAFE, 490UA412A4D,BOTH, 96-355/03:52:00:000, UNSTOW; CMD,6ASSAN,490UA412A6B,BOTH, 96-355/03:56:08:000, GV,153,IMM,231,

GV,153; CMD,7VECT, 490UA412A4E,BOTH, 96-355/03:56:10.000, 0,191.5,6.5,

0.0,0.0,0.0,96-350/00:00:00.000,MVR;

SEB,SCTEST,490UA412A23A,BOTH, 96-355/03:56:12.000, SYS1,NPERR; CMD,7TURN, 490UA412A4F,BOTH, 96-355/03:56:14.000, 1,MVR; MISC,NOTE, 490UA412A99A,, 96-355/04:00:00.000, ,START OF TURN;, CMD,7STAR, 490UA412A406A4A,BOTH 96-355/04:00:02.000, 7,1701,

278.813999,38.74; CMD,7STAR, 490UA412A406A4B,BOTH,96-355/04:00:04.000, 8,350,120.455999,

-39.8612; CMD,7STAR, 490UA412A406A4C,BOTH,96-355/04:00:06.000, 9,875,114.162,

5.341; CMD,7STAR, 490UA412A406A4D,BOTH,96-355/04:00:08.000, 10,159,27.239,

89.028999; CMD,7STAR, 490UA412A406A4E,BOTH,96-355/04:00:10.000, 11,0,0.0,0.0; CMD,7STAR, 490UA412A406A4F,BOTH,96-355/04:00:12.000, 21,0,0.0,0.0;

Houston, We have a problem ...

courtesy of NASA

• Quintuple fault occurs (three shorts, tank-line and pressure jacket burst, panel flies off).

• Mattingly works in ground simulator to identify new sequence handling severe power limitations.

• Mattingly identifies novel reconfiguration, exploiting LEM batteries for power.

• Swaggert & Lovell follow novel procedure to repair Apollo 13 lithium hydroxide unit.

What Makes this Difficult:Cassini Case Study

courtesy JPL

Reasoning through interactions is complex


Reconfiguring for a Failed EngineFuel tankFuel tankOxidizer tankOxidizer tank


Reconfiguring for a Failed Engine

Open fourvalves

Fuel tankFuel tankOxidizer tankOxidizer tank



Valve failsstuck closed

Open fourvalves




Fire backupengine

Valve failsstuck closed

Open fourvalves



Challenge: Thinking Through Interactions

Programmers must reason through system-wide interactions to generate codes for:

• command command confirmationconfirmation

• goal trackinggoal tracking• detecting anomaliesdetecting anomalies• isolating faultsisolating faults• diagnosing causesdiagnosing causes

• hardware reconfighardware reconfig• fault recoveryfault recovery• safingsafing• fault avoidancefault avoidance• control control

coordinationcoordination

Equally problematic at mission operations levelEqually problematic at mission operations level


Outline

• Motivation




Programmers generate breadth of functions from commonsense models in light of mission goals.

• Model-based Programming• Program by specifying commonsense, compositional

declarative models.

• Model-based Planning & Execution• Provide services that reason through each type of

system interaction from models.

• on the fly reasoning requires significant search & deduction within the reactive control loop.

Model-based Autonomy

courtesy of NASA




• Swaggert & Lovell work on Apollo 13 emergency rig lithium hydroxide unit.

Styles of Thinking Through Interactions




• Swaggert & Lovell work on Apollo 13 emergency rig lithium hydroxide unit.

• Multiple fault diagnosis of unexperienced failures.

• Mission planning and scheduling

• Hardware reconfiguration

• Scripted execution

Styles of Thinking Through Interactions


Example of a Model-based Agent:

• Goal-directed

• First time correct

• projective• reactive

• Commonsense models

• Heavily deductive

Scripts

component models

GoalsGoals

Diagnosis Diagnosis & Repair& Repair

Mission Mission ManagerManager

ScriptedScriptedExecutiveExecutive

Planner/Planner/SchedulerScheduler

Remote AgentRemote Agent

Mission-levelactions &resources


Conventional Wisdom: Reservations about Intelligent Embedded Systems

• “[For reactive systems] proving theorems is out of the question” [Agre & Chapman 87]


Many problems aren’t so hard


GenerateNon-conflicting

Successor

GenerateNon-conflicting

Successor

Candidates withCandidates withIncreasing costIncreasing cost

SATSAT

Explanationfor Conflicts

Explanationfor Conflicts

Developed RISC-like, deductive kernel (OPSAT)

How can general deduction achieve

reactive time scales?

Solutions


Transition Systems + Constraints + Probabilities

ClosedClosed

ValveValve

OpenOpen StuckStuckopenopen

StuckStuckclosedclosed

OpenOpen CloseClose

0. 010. 01

0. 010. 01

0.010.01

0.010.01

inflow = outflow = 0

Can model-based agents perform many different types of reasoning from a common model?

VDECU Op_State

On

Engine Op State

Burn_Ignition

BurnBurn_Termination

Shut_down

Off

Early_Prep Wait

Late_Prep


Outline

• Motivation




Real-Time Real-Time ExecutionExecution


Flight Flight H/WH/W

Flight Flight H/WH/WFault Fault

MonitorsMonitorsFault Fault

MonitorsMonitorsPlanning Experts Planning Experts (incl. Navigation)(incl. Navigation)Planning Experts Planning Experts (incl. Navigation)(incl. Navigation)

Remote Agent Architecture

Ground Ground SystemSystemGround Ground SystemSystem

RAX ManagerRAX Manager



Scripted Scripted ExecutiveExecutive


Remote AgentRemote AgentRAX_STARTRAX_START















Executive requests plan















Mission manager establishes goals, planner generates plan















Executive executes plan















Diagnosis system monitors and repairs

courtesy JPL

Walk Through of Cassini Saturn Orbital Insertion















Plan for Next Time Horizon


Thrust Goals

Attitude

Engine

Power


Thrust Goals

Attitude Point(a)

Engine Off

Off

Delta_V(direction=b, magnitude=200)

Power

Mission Manager Sets Goals over Horizon


Thrust Goals

Attitude Point(a)

Engine Off

Off


Power

Planner StartsPlanner Starts


Thrust Goals

Attitude Point(a)

Engine Thrust (b, 200) Off

Off


Power


Thrust Goals

Attitude Point(a)

Engine


Power

Thrust (b, 200) Off

Off


Thrust Goals

Attitude Point(a)

Engine


Power

Off

Off Thrust (b, 200)


Point(b)

Thrust Goals

Attitude Point(a)

Engine Off


Power

Thrust (b, 200) Off


Thrust Goals

Attitude Point(a) Point(b)

Engine Thrust (b, 200)Off


Power

Off


Thrust Goals

Attitude Point(a) Point(b)

Engine Thrust (b, 200)Warm Up Off

Off


Power


Thrust Goals

Attitude Point(a) Point(b) Turn(b,a)

Engine Thrust (b, 200)Warm Up Off

Off


Power


Thrust Goals

Attitude Turn(a,b)Point(a) Point(b) Turn(b,a)


Off


Power

Warm Up


Thrust Goals

Attitude Turn(a,b)Point(a) Point(b) Turn(b,a)


Off


Power

Warm Up

Plan Completed!Plan Completed!


Plan Model Fragment UsedPlan Model Fragment Used

Thrust Goals

Attitude

Engine Thrust (b, 200)


Power

contains


Thrust Goals

Attitude Point(b)



Power

Warm Up

meets met_by

contained_by

contained_by

equals

Plan Model Fragment UsedPlan Model Fragment Used


Plans Allow Temporal FlexibilityThrough Least Committment















The executive executes and decomposes the plan


Executing Temporal Plans

[130,170]]

<0, 0>

[0, 300]

• Propagate temporal constraints• Select enabled events• Terminate preceding activities• Run next activities


Propagating Timing Constraints Can Be Costly

EXECUTIVE

CONTROLLED SYSTEM


EXECUTIVE

CONTROLLED SYSTEM

Propagating Timing Constraints Can Be Costly


EXECUTIVE

CONTROLLED SYSTEM

Solution: Compile Temporal Constraints to an Efficient Network















Execution is monitored:Failures are diagnosed and repaired


Programmers and operators must reason through system-wide interactions to generate codes for:

Reconfiguring ModesIdentifying Modes

• monitoringmonitoring• tracking goalstracking goals• confirming confirming

commandscommands• detecting anomaliesdetecting anomalies• diagnosing faults diagnosing faults

• reconfiguring reconfiguring hardwarehardware

• coordinating control coordinating control policies policies

• recovering from faultsrecovering from faults• avoiding failuresavoiding failures

Model-based Execution of Activities


Model-based Execution asStochastic Optimal Control

Controller

Plant

modeidentification

mode reconfiguration

s’(t)

(t)

ffs (t)

gg

o(t)

Model

Livingstone

Goals


Closed

Open Stuckopen

Stuckclosed

OpenCloseCost 5

Prob .9

Models• modes engage physical processes• probabilistic automata for dynamics

Vlv = closed => Outflow = 0;

vlv=open => Outflow = Mz

+(inflow);

vlv=stuck open => Outflow = Mz

+(inflow);

vlv=stuck closed=> Outflow = 0;


Mode Estimation and Diagnosis

Observe“no thrust”

Find most likely reachable states consistent with observations.


Mode Reconfiguration and RepairGoal: Achieve Thrust


Goal: Achieve Thrust

Mode Reconfiguration and Repair

courtesy JPL

Ames-JPL NewMaap: New Millennium Advanced Autonomy Prototype

July - November, 1995

courtesy JPL

Started: January 1996Launch: Fall 1998


Remote Agent Experiment

May 17-18th experiment• Generate plan for course correction and thrust • Diagnose camera as stuck on

– Power constraints violated, abort current plan and replan• Perform optical navigation• Perform ion propulsion thrust

May 21th experiment.• Diagnose faulty device and

– Repair by issuing reset. • Diagnose switch sensor failure.

– Determine harmless, and continue plan. • Diagnose thruster stuck closed and

– Repair by switching to alternate method of thrusting. • Back to back planning

See rax.arc.nasa.gov

“With autonomy we declare that no sphere is off limits. We will send our spacecraft to search beyond the horizon, accepting that we cannot directly control them, and relying on them to tell the tale.”

Bob Rasmussen ArchitectJPL MissionData System

robotic space explorers: to boldly go where no ai system has gone before

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