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Robotic Space Explorers

Robotic Space Explorers. Brian C. Williams Space Systems Lab & Artificial Intelligence Lab, MIT. Marskokhod at NASA Ames research center. Smart Buildings at CMU & Xerox PARC. Ecological Life Support For Mars Exploration. Portable Satellite Assistant. Courtesy of Yuri Gawdiak, NASA Ames.

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Robotic Space Explorers

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  1. Robotic Space Explorers Brian C. Williams Space Systems Lab & Artificial Intelligence Lab, MIT

  2. Marskokhod at NASA Ames research center

  3. Smart Buildings at CMU & Xerox PARC

  4. Ecological Life SupportFor Mars Exploration

  5. Portable Satellite Assistant Courtesy of Yuri Gawdiak, NASA Ames

  6. Robotic Webs

  7. Unmanned Air Vehicles

  8. Intelligence Embedded at all Levels • Behavior-based robotics: Subsumption • Reinforcement learning and MDPS • Classical planning and execution • Model-based diagnosis and execution • Mission-level planning • Robotic path planning • Probabilistic monitoring and • Decision-theoretic planning • Multi-agent coordination Increased Reasoning

  9. To Boldly Go Where No AI System Has Gone Before A Story of Survival

  10. Started: January 1996 Launch: Fall 1998 courtesy JPL

  11. Douglas Bernard JPL Steve Chien JPL Greg Dorais Ames Julia Dunphy JPL Dan Dvorak JPL Chuck Fry Ames Ed Gamble JPL Erann Gat JPL Othar Hansson Thinkbank Jordan Hayes Thinkbank Bob Kanefsky Ames Ron Keesing Ames James Kurien Ames Bill Millar Ames Sunil Mohan Formida Paul Morris Ames Remote Agent Team Members • Nicola Muscettola Ames • Pandurang Nayak Ames • Barney Pell Ames • Chris Plaunt Apple • Gregg Rabideau JPL • Kanna Rajan Ames • Nicolas Rouquette JPL • Scott Sawyer LMMS • Rob Sherwood JPL • Reid Simmons CMU • Ben Smith JPL • Will Taylor Ames • Hans Thomas Ames • Michael Wagner 4th Planet • Greg Whelan CMU • Brian C. Williams Ames • David Yan Stanford

  12. I am a HAL 9000 computer production number three. I became operational at the H.A.L. plant in Urbana, Illinois on January 12, 1997.

  13. courtesy NASA International Space Station 1998-2002

  14. ``Our vision in NASA is to open the Space Frontier. When people think of space, they think of rocket plumes and the space shuttle. But the future of space is in information technology. We must establish a virtual presence, in space, on planets, in aircraft and spacecraft.’’ - Daniel S. Goldin, NASA Administrator Sacramento, California, May 29, 1996 Motive: Astrobiology & Origins Programs Means: New Millennium Program Smarts: Autonomous Reasoning

  15. Motive: Primitive life on Early Mars? 1997: Mars Pathfinder and Sojourner courtesy JPL

  16. New Means Mars Pathfinder, 1997 courtesy JPL

  17. New Means: Mars Airplane courtesy NASA Ames courtesy NASA Lewis

  18. Motive: life under Europa? Cryobot & Hydrobot courtesy JPL

  19. Formation Flying Optical Interferometer (ST3) Motive: Earth-like Planets Around Other Stars? courtesy JPL

  20. Four launches in 7 months Mars Climate Orbiter: 12/11/98 Mars Polar Lander: 1/3/99 QuickSCAT: 6/19/98 Stardust: 2/7/99 courtesy of JPL

  21. Traditional spacecraft commanding

  22. How Will They Survive? • Vanished: • Mars Observer • Mars Polar Lander • Miscommanded • Clementine • Mars Climate Orbiter courtesy of JPL

  23. STS-93 Hydrogen Leak • Symptoms: • Engine temp sensor high • LOX level low • GN&C detects low thrust • H2 level low (???) • Problem: Liquid hydrogen leak • Effect: • LH2 used to cool engine • Engine runs hot • Consumes more LOX

  24. Intelligent Embedded Systems: Cassini • 7 year cruise • ~ 150 - 300 ground operators • ~ 1 billion $ • 7 years to build Faster, Better, Cheaper • 150 million $ • 2 year build • 0 ground ops Cassini Maps Titan courtesy JPL

  25. Ames-JPL NewMaap: New Millennium Advanced Autonomy Prototype • no Earth Comm • ~ 1 hr insertion window • engines idle for several years • moves through ring plane July - November, 1995 courtesy JPL

  26. Reconfiguring for a Failed Engine Oxidizer tank Fuel tank Open four valves Valve fails stuck closed Fire backup engine

  27. AI in the pre-90’s: Reservations about Embedded Systems being Intelligent • “[For reactive systems] proving theorems is out of the question” [Agre & Chapman 87] • ``Diagnostic reasoning from a tractable model is largely well understood. [However] we don’t know how to model complex behavior...’’[Davis & Hamscher 88] • “[Commonsense] equations are far too general for practical use.” [Sacks & Doyle 91]

  28. 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 work on Apollo 13 emergency rig lithium hydroxide unit. Houston, We have a problem ... courtesy of NASA

  29. Challenge: Thinking Through Interactions Programmers must reason through system-wide interactions to generate codes for: • command confirmation • goal tracking • detecting anomalies • isolating faults • diagnosing causes • hardware reconfig • fault recovery • safing • fault avoidance • control coordination Equally problematic at mission operations level

  30. Model-based Autonomy • Programmers generate breadth of functions from commonsense models in light of mission goals. • Model-based Programming • Program by specifying commonsense, compositional declarative models. • Model-directed 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.

  31. Valve Stuck open 0.01 Open 0. 01 Open Close 0. 01 Stuck closed Closed 0.01 inflow = outflow = 0 Towards a Unified Model Hardware Commanding & Failure Model Mission Operations Model Transition Systems + Constraints + Probabilities

  32. Fast Search: Deep Blue beats Kasparov by brute force.

  33. 1 . 0 0 . 8 2 0 2 U N S A T 0 . 6 P h a s e 0 . 4 S A T P h a s e 0 . 2 0 3 4 5 6 7 M / N Fraction of Formulae Unsatisfied 1 . 0 0 . 8 0 . 6 0 . 4 0 . 2 0 . 0 - 1 0 0 1 0 2 0 Many problems aren’t so hard 1 0 0 5 0 1 4 0 2 4 P h a s e T r a n s i t i o n f o r 3 - S A T , N = 1 2 t o 1 0 0 D = = a t 1 4 a . . 5 1 R 7 e , s c a l e d U s i n g c a n S , ( K c M i i r e a k n y p c a 1 e t 9 r 9 i c 4 k ) a n d S e l m a n ,

  34. General Deduction Can Achieve Reactive Time Scales Many problems aren’t so hard RISC-like, deductive kernel 4-sat cost Agenda TMS 25 var. FOUND UNSOLVABLE SOLUTION FOUND generate successor conflict database Average constraints per variable

  35. 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 work on Apollo 13 emergency rig lithium hydroxide unit. Services For Thinking Through Interactions • Multiple fault diagnosis of unexperienced failures. • Mission planning and scheduling • Hardware reconfiguration • Scripted execution

  36. Remote Agent Scripted Executive Mission Manager Planner/ Scheduler Diagnosis & Reconfig Remote Agent Architecture Ground System RAX_START RAX_START Real-Time Execution RAX Manager Flight H/W Fault Monitors Planning Experts (incl. Navigation)

  37. Ames-JPL NewMaap: New Millennium Advanced Autonomy Prototype July - November, 1995 courtesy JPL

  38. Delta_V(direction=b, magnitude=200) Point(a) Mission Manager Sets Goals Thrust Goals Power Attitude Off Engine Off

  39. Delta_V(direction=b, magnitude=200) Point(a) Point(b) Turn(b,a) Turn(a,b) Off Plan! Thrust Goals Power Attitude Thrust (b, 200) Engine Off Warm Up

  40. Planner Models • Objects • state-variables • tokens • Constraints • compatibilities • functional dependencies

  41. Delta_V(direction=b, magnitude=200) Compatibility Thrust Goals Power contains Attitude Thrust (b, 200) Engine

  42. Delta_V(direction=b, magnitude=200) Off Compatibility Thrust Goals Power equals contained_by Point(b) Attitude contained_by meets met_by Thrust (b, 200) Engine Warm Up

  43. Plan has flaws Plan is consistent Planning/Scheduling Cycle PLAN NO Uninstantiated compatibility . . . Heuristics Instantiate compatibility . . . Backtrack Schedule token NO YES

  44. Types of Plan Flaws • Un-instantiated compatibilities • subgoaling • Un-inserted tokens • Under-constrained parameter • Gaps in scheduling horizon

  45. Plan Generates A Simple Temporal Constraint Network       

  46. [0, 300]   <0, 0>  [130,170]] Executing Temporal Plans • Propagate time • Select enabled events • Terminate preceding tokens • Run next tokens

  47. Time Propagation Can Be Costly EXECUTIVE CONTROLLED SYSTEM

  48. Compile to Efficient Network EXECUTIVE CONTROLLED SYSTEM

  49. Model-based Execution of Tokens Programmers and operators must reason through system-wide interactions to generate codes for: • monitoring • tracking goals • confirming commands • detecting anomalies • diagnosing faults • reconfiguring hardware • coordinating control policies • recovering from faults • avoiding failures Identifying Modes Reconfiguring Modes

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