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Robotic Space Explorers: To Boldly Go Where No AI System Has Gone Before. A Story of Survival 16.412J/6.834J September 19, 2001. Readings and Assignment. Model-based Agents:
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Robotic Space Explorers:To Boldly Go Where No AI System Has Gone Before A Story of Survival 16.412J/6.834J September 19, 2001
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
A Capable Robotic Explorer: Cassini Faster, Better, Cheaper • 150 million $ • 2 year build • 0 ground ops • 7 year cruise • ~ 150 - 300 ground operators • ~ 1 billion $ • 7 years to build Cassini Maps Titan courtesy JPL
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: 12/11/98 Mars Polar Lander: 1/3/99 QuickSCAT: 6/19/98 Stardust: 2/7/99 courtesy 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…
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. Houston, We have a problem ... courtesy of NASA
What Makes this Difficult: Cassini Case Study courtesy JPL
Reconfiguring for a Failed Engine Oxidizer tank Fuel tank
Reconfiguring for a Failed Engine Oxidizer tank Fuel tank Open four valves
Reconfiguring for a Failed Engine Oxidizer tank Fuel tank Open four valves Valve fails stuck closed
Reconfiguring for a Failed Engine Oxidizer tank Fuel tank Open four valves Valve fails stuck closed Fire backup engine
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
Outline • Motivation • Model-based autonomous systems • Remote Agent Example
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-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.
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 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 • Multiple fault diagnosis of unexperienced failures. • Mission planning and scheduling • Hardware reconfiguration • Scripted execution
Example of a Model-based Agent: Goals Scripts • Goal-directed • First time correct • projective • reactive • Commonsense models • Heavily deductive Remote Agent Scripted Executive Mission Manager Planner/ Scheduler Diagnosis & Repair Mission-level actions & resources component models
Conventional Wisdom: Reservations about Intelligent Embedded Systems • “[For reactive systems] proving theorems is out of the question” [Agre & Chapman 87]
How can general deduction achieve reactive time scales? Candidates withIncreasing cost SAT Solutions Generate Non-conflicting Successor Explanation for Conflicts Developed RISC-like, deductive kernel (OPSAT)
Can model-based agents perform many different types of reasoning from a common model? Valve Transition Systems + Constraints + Probabilities Stuck open 0.01 Open 0. 01 Open Close 0. 01 Stuck closed Closed 0.01 inflow = outflow = 0
Outline • Motivation • Model-based autonomous systems • Remote Agent Example
Remote Agent Scripted Executive Mission Manager Planner/ Scheduler Diagnosis & Repair Remote Agent Architecture Ground System RAX_START RAX_START Real-Time Execution RAX Manager Flight H/W Fault Monitors Planning Experts (incl. Navigation)
Executive requests plan Remote Agent Ground System Scripted Executive Mission Manager RAX_START RAX_START Real-Time Execution Planner/ Scheduler Diagnosis & Repair RAX Manager Flight H/W Fault Monitors Planning Experts (incl. Navigation)
Mission manager establishes goals, planner generates plan Remote Agent Ground System Scripted Executive Mission Manager RAX_START RAX_START Real-Time Execution Planner/ Scheduler Diagnosis & Repair RAX Manager Flight H/W Fault Monitors Planning Experts (incl. Navigation)
Executive executes plan Remote Agent Ground System Scripted Executive Mission Manager RAX_START RAX_START Real-Time Execution Planner/ Scheduler Diagnosis & Repair RAX Manager Flight H/W Fault Monitors Planning Experts (incl. Navigation)
Diagnosis system monitors and repairs Remote Agent Ground System Scripted Executive Mission Manager RAX_START RAX_START Real-Time Execution Planner/ Scheduler Diagnosis & Repair RAX Manager Flight H/W Fault Monitors Planning Experts (incl. Navigation)
Walk Through of Cassini Saturn Orbital Insertion courtesy JPL
Plan for Next Time Horizon Remote Agent Ground System Scripted Executive Mission Manager RAX_START RAX_START Real-Time Execution Planner/ Scheduler Diagnosis & Repair RAX Manager Flight H/W Fault Monitors Planning Experts (incl. Navigation)
Thrust Goals Power Attitude Engine
Delta_V(direction=b, magnitude=200) Point(a) Mission Manager Sets Goals over Horizon Thrust Goals Power Attitude Off Engine Off
Delta_V(direction=b, magnitude=200) Point(a) Planner Starts Thrust Goals Power Attitude Off Engine Off
Delta_V(direction=b, magnitude=200) Point(a) Thrust Goals Power Attitude Thrust (b, 200) Off Engine Off
Delta_V(direction=b, magnitude=200) Point(a) Off Thrust Goals Power Attitude Thrust (b, 200) Engine Off
Delta_V(direction=b, magnitude=200) Point(a) Thrust (b, 200) Off Thrust Goals Power Attitude Engine Off
Delta_V(direction=b, magnitude=200) Point(a) Thrust (b, 200) Off Thrust Goals Power Attitude Engine Off
Delta_V(direction=b, magnitude=200) Point(a) Thrust (b, 200) Off Thrust Goals Power Point(b) Attitude Engine Off
Delta_V(direction=b, magnitude=200) Point(a) Off Thrust Goals Power Point(b) Attitude Thrust (b, 200) Engine Off
Thrust Goals Delta_V(direction=b, magnitude=200) Power Point(b) Point(a) Attitude Thrust (b, 200) Off Engine Off Warm Up
Delta_V(direction=b, magnitude=200) Point(a) Point(b) Turn(b,a) Off Thrust Goals Power Attitude Thrust (b, 200) Engine Off Warm Up
Delta_V(direction=b, magnitude=200) Turn(b,a) Point(a) Point(b) Off Thrust Goals Power Attitude Thrust (b, 200) Engine Off Warm Up
Delta_V(direction=b, magnitude=200) Point(b) Turn(b,a) Point(a) Turn(a,b) Off Thrust Goals Power Attitude Thrust (b, 200) Engine Off Warm Up
Delta_V(direction=b, magnitude=200) Point(a) Point(b) Turn(b,a) Turn(a,b) Off Thrust Goals Power Attitude Thrust (b, 200) Engine Off Warm Up
Delta_V(direction=b, magnitude=200) Point(a) Point(b) Turn(b,a) Turn(a,b) Off Plan Completed! Thrust Goals Power Attitude Thrust (b, 200) Engine Off Warm Up
Delta_V(direction=b, magnitude=200) Plan Model Fragment Used Thrust Goals Power contains Attitude Thrust (b, 200) Engine