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MIT 16 412J - Robust Task Execution

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Robust Task Execution: 1 Brian C. Williams 16.412J/6.834J March 14th, 2005 Robust Task Expansion Projective Task Expansion Goals Dynamic Scheduling and Task Dispatch Task Dispatch Temporal Plan CommandsObservations Modes Mission Goals and Environment Constraints Temporal Network Solver Temporal Planner Initial Conditions Procedural and Model-based Model-based Executive S Plant Obs Cntrl Embedded Programs S Continuous Reactive Commanding Continuous Mode/State Estimation Model Create Languages that are: • Commanded with desired state Desiderata: Robust Task-level Execution Model-based • Suspicious •Monitor intentions and plans • Self-Adaptive • Exploits and generates contingencies • Anticipatory • Predicts, plans and verifies into future •State Aware • Fault Aware •Reasons about and responds to failure Outline • Safe Procedural Execution • Model-Predictive Dispatch • Model-based Reactive Planning Robust Task Execution: RAPS [Firby PhD] • RAPS Monitors Success Against Spec (define-rap (move-to thing place) (succeed (LOCATION thing place)) (method (context (and (LOCATION thing loc) (not (= loc UNKNOWN)))) (task-net (t0 (goto loc) ((TRUCK -LOCATION loc) for t1)) (t1 (pickup thing)((TRUCK -HOLDING thing) for t2) ((TRUCK -HOLDING thing) for t3)) (t2 (goto place) ((TRUCK-LOCATION place) for t3)) (t3 (putdown thing)))) (method (context (LOCATION thing UNKNOWN)) (task-net (t0 (goto WAREHOUSE))))) Robust Task Execution: RAPS [Firby PhD] • RAPS Exploits contingencies by performingfunctionally redundant method selection (define-rap (move -to thing place) (succeed (LOCATION thing place)) (method (context(and (LOCATION thing loc) (not (= loc UNKNOWN)))) (task-net (t0 (goto loc) ((TRUCK -LOCATION loc) for t1)) (t1 (pickup thing)((TRUCK -HOLDING thing) for t2) ((TRUCK -HOLDING thing) for t3)) (t2 (goto place) ((TRUCK-LOCATION place) for t3)) (t3 (putdown thing)))) (method (context (LOCATION thing UNKNOWN)) (task-net (t0 (goto WAREHOUSE))))) 1Deductive ControllerModeEstimationModeReconfiguration• RAPS Exploits contingencies by performing functionally redundant method selection – Methods are chosen based on the current situation. – If a method fails, another is tried instead. – Tasks do not complete until satisfied. – Methods can include monitoring subtasks to deal with contingencies and opportunities. �Methods selected reactively �Model -predictive dispatch �Goals explicitly observable and controllable �Model -based execution Robust Task Execution: RAPS [Firby PhD] Control Sequencer Environment Model CommandsObservations Control Program Kirk Model-based ExecutiveRMPL Model-based Program location goalslocation estimates Selects consistent threads of activity from redundant methods Tracks location Finds least cost paths � Executes concurrently � Preempts � non -deterministic choice � A[l,u ] timing � A at l location HOMEHOMET W O Enroute COLLECTION POINTCOLLECTION POINTRENDEZVOUSRENDEZVOUSDiverge SCIENCE AREA 1’SCIENCE AREA 1’SCIENCE AREA 3SCIENCE AREA 3Landing Site: ABC Landing Site: XYZ O N E SCIENCE AREA 1SCIENCE AREA 1Executive • pre-plans activities • pre-plans paths • dynamically schedules [Tsmardinos et al.] Plant Schedules and Dispatches Activities Dynamically Outline • Safe Procedural Execution • Model-Predictive Dispatch – Model-based Programming – Temporal Plan Networks (TPN) – Activity Planning (Kirk) – Unifying Activity and Path Planning • Model-based Reactive Planning Example: Cooperative Mars Exploration How do we coordinate heterogeneous teams of orbiters, rovers and air vehicles to perform globally optimal science exploration? Properties: � Teams exploit a hierarchy of complex strategies. � Maneuvers are temporally coordinated. � Novel events occur during critical phases. � Quick responses draw upon a library of contingencies. � Selected contingencies must respect timing constraints. HOMEHOMETWO EnrouteCOLLECTION POINTCOLLECTION POINTRENDEZVOUSRENDEZVOUSDiverge SCIENCE AREA 1’SCIENCE AREA 1’SCIENCE AREA 3SCIENCE AREA 3Landing Site: ABC Landing Site: XYZ ONE SCIENCE AREA 1SCIENCE AREA 1Example: Cooperative Mars Exploration Reactive Model-based Programming Idea: Describe team behaviors by starting with a rich concurrent , embedded programming language (RMPL,TCC, Esterel): � c � If c next A � Unless c next A � A, B � Always A • Sensing/actuation activities • Conditional execution • Preemption • Full concurrency • Iteration � A [l,u] • Timing Add temporal constraints: � Choose {A, B} • Contingency Add choice (non-deterministic or decision-theoretic): 2Example Enroute Activity: Enroute RendezvousRendezvous Rescue AreaRescue AreaCorridor 2 Corridor 1 RMPL for Group-Enroute Activities: Group-Enroute()[l,u] = { choose { do { Group-Traverse-Path(PATH1_1,PATH1_2,PATH1_3,RE_POS)[l*90%,u*90%]; } maintaining PATH1_OK, do { Group-Traverse-Path(PATH2_1,PATH2_2,PATH2_3,RE_POS)[l*90%,u*90%]; } maintaining PATH2_OK }; { Group-Transmit(OPS,ARRIVED)[0,2], do { Group-Wait(HOLD1,HOLD2)[0,u*10%] } watching PROCEED } } RMPL for Group-Enroute Sequentiality: Group-Enroute()[l,u] = { choose { Concurrency : do { Group-Traverse-Path(PATH1_1,PATH1_2,PATH1_3,RE_POS)[l*90%,u*90%]; } maintaining PATH1_OK, do { Group-Traverse-Path(PATH2_1,PATH2_2,PATH2_3,RE_POS)[l*90%,u*90%]; } maintaining PATH2_OK } ; { Group-Transmit(OPS,ARRIVED)[0,2], do { Group-Wait(HOLD1,HOLD2)[0,u*10%] } watching PROCEED } } RMPL for Group-Enroute Group-Enroute()[l,u] = { choose { do { Group-Traverse-Path(PATH1_1,PATH1_2,PATH1_3,RE_POS)[l*90%,u*90%]; } maintaining PATH1_OK, do { Group-Traverse-Path(PATH2_1,PATH2_2,PATH2_3,RE_POS)[l*90%,u*90%]; } maintaining PATH2_OK }; { Group-Transmit(OPS,ARRIVED)[0,2], do { Group-Wait(HOLD1,HOLD2)[0,u*10%] } watching PROCEED } } RMPL for Group-Enroute ConditionalityGroup-Enroute()[l,u] = { choose { and Preemption: do { Group-Traverse-Path(PATH1_1,PATH1_2,PATH1_3,RE_POS)[l*90%,u*90%]; } maintaining PATH1_OK, do { Group-Traverse-Path(PATH2_1,PATH2_2,PATH2_3,RE_POS)[l*90%,u*90%]; } maintaining PATH2_OK }; { Group-Transmit(OPS,ARRIVED)[0,2], do { Group-Wait(HOLD1,HOLD2)[0,u*10%] } watching PROCEED } } RMPL for Group-Enroute Temporal Constraints:Group-Enroute()[l,u] = { choose { do { Group-Fly-Path(PATH1_1,PATH1_2,PATH1_3,RE_POS)[l*90%,u*90%]; } maintaining PATH1_OK, do { Group-Fly-Path(PATH2_1,PATH2_2,PATH2_3,RE_POS)[l*90%,u*90%]; } maintaining


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