1. Robotic Space Explorers: To Boldly Go Where No AI System Has Gone Before A Story of Survival 16.412J/6.834J September 19, 2001

2. 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. Remote Agent: to Boldy Go Where No AI System Has Gone Before, 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.Path Planning Using Lazy PRM,

3. Copyright B. Williams 16.412J/6.834J, Fall 01 Outline Motivation Model-based autonomous systems Remote Agent Example

4. 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

5. 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

6. Copyright B. Williams 16.412J/6.834J, Fall 01 Four launches in 7 months Mars Climate Orbiter: 12/11/98 Mars Polar Lander: 1/3/99 Stardust: 2/7/99 QuickSCAT: 6/19/98 courtesy of JPL

7. Copyright B. Williams 16.412J/6.834J, Fall 01 Miscommanded: Mars Climate Orbiter Clementine courtesy of JPL Spacecraft should be embodied with a survival instinct

8. Copyright B. Williams 16.412J/6.834J, Fall 01 Vanished: Mars Polar Lander Mars Observer courtesy of JPL Spacecraft require commonsense…

9. Copyright B. Williams 16.412J/6.834J, Fall 01 Traditional spacecraft commanding

10. 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.

11. What Makes this Difficult: Cassini Case Study courtesy JPL

12. Reasoning through interactions is complex

13. Copyright B. Williams 16.412J/6.834J, Fall 01 Reconfiguring for a Failed Engine Fuel tank Oxidizer tank

14. Copyright B. Williams 16.412J/6.834J, Fall 01 Reconfiguring for a Failed Engine Open four valves Fuel tank Oxidizer tank

15. Copyright B. Williams 16.412J/6.834J, Fall 01 Reconfiguring for a Failed Engine Valve fails stuck closed Open four valves Fuel tank Oxidizer tank

16. Copyright B. Williams 16.412J/6.834J, Fall 01 Reconfiguring for a Failed Engine Fire backup engine Valve fails stuck closed Open four valves Fuel tank Oxidizer tank

17. Copyright B. Williams 16.412J/6.834J, Fall 01 Challenge: Thinking Through Interactions Programmers must reason through system-wide interactions to generate codes for: command confirmationcommand confirmation goal tracking goal tracking detecting anomalies detecting anomalies isolating faults isolating faults diagnosing causes diagnosing causes hardware reconfig hardware reconfig fault recovery fault recovery safing safing fault avoidance fault avoidance control coordination control coordination Equally problematic at mission operations level

18. Copyright B. Williams 16.412J/6.834J, Fall 01 Outline Motivation Model-based autonomous systems Remote Agent Example

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

20. 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 work on Apollo 13 emergency rig lithium hydroxide unit. Styles of Thinking Through Interactions

21. 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. Multiple fault diagnosis of unexperienced failures. Mission planning and scheduling Hardware reconfiguration Scripted execution Styles of Thinking Through Interactions

22. Copyright B. Williams 16.412J/6.834J, Fall 01 Example of a Model-based Agent: Goal-directed First time correct projective reactive Commonsense models Heavily deductive Scripts component models Goals Diagnosis & Repair Mission Manager ScriptedExecutive Planner/Scheduler Remote Agent Mission-level actions & resources

23. Copyright B. Williams 16.412J/6.834J, Fall 01 Conventional Wisdom: Reservations about Intelligent Embedded Systems “[For reactive systems] proving theorems is out of the question” [Agre & Chapman 87]

24. Copyright B. Williams 16.412J/6.834J, Fall 01 Many problems aren’t so hard

25. Copyright B. Williams 16.412J/6.834J, Fall 01 Generate Non-conflicting Successor Generate Non-conflicting Successor Candidates with Increasing cost SAT Explanation for Conflicts Explanation for Conflicts Developed RISC-like, deductive kernel (OPSAT) How can general deduction achieve reactive time scales? Solutions

26. Copyright B. Williams 16.412J/6.834J, Fall 01 Transition Systems + Constraints + Probabilities Closed Valve Open Stuckopen Stuckclosed OpenClose 0. 01 0.01 0.01 inflow = outflow = 0 Can model-based agents perform many different types of reasoning from a common model?

27. Copyright B. Williams 16.412J/6.834J, Fall 01 Outline Motivation Model-based autonomous systems Remote Agent Example

28. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Remote Agent Architecture Ground System RAX Manager Diagnosis & Repair Mission Manager Scripted Executive Planner/Scheduler Remote Agent RAX_START

29. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager ScriptedExecutive Planner/Scheduler Remote Agent RAX_START Executive requests plan

30. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager Scripted Executive Planner/Scheduler Remote Agent RAX_START Remote Agent Architecture

31. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager Scripted Executive Planner/Scheduler Remote Agent RAX_START Mission manager establishes goals, planner generates plan

32. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager ScriptedExecutive Planner/Scheduler Remote Agent RAX_START Executive executes plan

33. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager Scripted Executive Planner/Scheduler Remote Agent RAX_START Diagnosis system monitors and repairs

34. courtesy JPL Walk Through of Cassini Saturn Orbital Insertion

35. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager Scripted Executive Planner/Scheduler Remote Agent RAX_START Plan for Next Time Horizon

36. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Engine Power

37. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Engine Off Delta_V(direction=b, magnitude=200) Power Mission Manager Sets Goals over Horizon

38. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Engine Off Delta_V(direction=b, magnitude=200) Power Planner Starts

39. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Engine Thrust (b, 200) Off Delta_V(direction=b, magnitude=200) Power

40. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Engine Delta_V(direction=b, magnitude=200) Power Thrust (b, 200) Off

41. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Engine Delta_V(direction=b, magnitude=200) Power Thrust (b, 200) Off

42. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Engine Delta_V(direction=b, magnitude=200) Power Off Thrust (b, 200)

43. Copyright B. Williams 16.412J/6.834J, Fall 01 Point(b) Thrust Goals Attitude Point(a) EngineOff Delta_V(direction=b, magnitude=200) Power Thrust (b, 200) Off

44. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Point(b) Engine Thrust (b, 200) Off Delta_V(direction=b, magnitude=200) Power Off

45. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a) Point(b) Engine Thrust (b, 200) Warm Up Off Delta_V(direction=b, magnitude=200) Power

46. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a)Point(b)Turn(b,a) Engine Thrust (b, 200) Warm Up Off Delta_V(direction=b, magnitude=200) Power

47. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(a)Point(b) Turn(b,a) Engine Thrust (b, 200) Warm Up Off Delta_V(direction=b, magnitude=200) Power

48. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Turn(a,b) Point(a) Point(b)Turn(b,a) Engine Thrust (b, 200) Off Delta_V(direction=b, magnitude=200) Power Warm Up

49. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Turn(a,b) Point(a)Point(b)Turn(b,a) Engine Thrust (b, 200) Off Delta_V(direction=b, magnitude=200) Power Warm Up

50. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Turn(a,b) Point(a)Point(b)Turn(b,a) Engine Thrust (b, 200) Off Delta_V(direction=b, magnitude=200) Power Warm Up Plan Completed!

51. Copyright B. Williams 16.412J/6.834J, Fall 01 Plan Model Fragment Used Thrust Goals Attitude Engine Thrust (b, 200) Delta_V(direction=b, magnitude=200) Power contains

52. Copyright B. Williams 16.412J/6.834J, Fall 01 Thrust Goals Attitude Point(b) Engine Thrust (b, 200) Off Delta_V(direction=b, magnitude=200) Power Warm Up meets met_by contained_by equals Plan Model Fragment Used

53. Copyright B. Williams 16.412J/6.834J, Fall 01 Plans Allow Temporal Flexibility Through Least Committment       

54. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager ScriptedExecutive Planner/Scheduler Remote Agent RAX_START The executive executes and decomposes the plan

55. Copyright B. Williams 16.412J/6.834J, Fall 01 Executing Temporal Plans [130,170]] [0, 300]   Propagate temporal constraints Select enabled events Terminate preceding activities Run next activities

56. Copyright B. Williams 16.412J/6.834J, Fall 01 Propagating Timing Constraints Can Be Costly EXECUTIVE CONTROLLED SYSTEM

57. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Propagating Timing Constraints Can Be Costly

58. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Propagating Timing Constraints Can Be Costly

59. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Propagating Timing Constraints Can Be Costly

60. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Propagating Timing Constraints Can Be Costly

61. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Propagating Timing Constraints Can Be Costly

62. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Solution: Compile Temporal Constraints to an Efficient Network

63. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Solution: Compile Temporal Constraints to an Efficient Network

64. Copyright B. Williams 16.412J/6.834J, Fall 01 EXECUTIVE CONTROLLED SYSTEM Solution: Compile Temporal Constraints to an Efficient Network

65. Copyright B. Williams 16.412J/6.834J, Fall 01 Real-Time Execution Flight H/W Fault Monitors Planning Experts (incl. Navigation) Ground System RAX Manager Diagnosis & Repair Mission Manager Scripted Executive Planner/Scheduler Remote Agent RAX_START Execution is monitored: Failures are diagnosed and repaired

66. Copyright B. Williams 16.412J/6.834J, Fall 01 Programmers and operators must reason through system-wide interactions to generate codes for: Reconfiguring ModesIdentifying Modes monitoring monitoring tracking goals tracking goals confirming commands confirming commands detecting anomalies detecting anomalies diagnosing faults diagnosing faults reconfiguring hardwarereconfiguring hardware coordinating control policies coordinating control policies recovering from faults recovering from faults avoiding failures avoiding failures Model-based Execution of Activities

67. Copyright B. Williams 16.412J/6.834J, Fall 01 Model-based Execution as Stochastic Optimal Control Controller Plant mode identification mode reconfiguration s’(t)  (t) f f s (t) g g o(t) Model Livingstone Goals

68. Copyright B. Williams 16.412J/6.834J, Fall 01 Closed Open Stuck open Stuck closed Open Close Cost 5 Prob.9 Models modes engage physical processes probabilistic automata for dynamics Vlv = closed => Outflow = 0; vlv=open => Outflow = M z + (inflow); vlv=stuck open => Outflow = M z + (inflow); vlv=stuck closed=> Outflow = 0;

69. Copyright B. Williams 16.412J/6.834J, Fall 01 Mode Estimation and Diagnosis Observe “no thrust” Find most likely reachable states consistent with observations.

70. Copyright B. Williams 16.412J/6.834J, Fall 01 Mode Reconfiguration and Repair Goal: Achieve Thrust

71. Copyright B. Williams 16.412J/6.834J, Fall 01 Goal: Achieve Thrust Mode Reconfiguration and Repair

72. Copyright B. Williams 16.412J/6.834J, Fall 01 Goal: Achieve Thrust Mode Reconfiguration and Repair

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

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

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

76. “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 Architect JPL Mission Data System