SUO/PDA ARPI Fall 1999 Workshop 1ARPI Small Unit Operations SUO/PDA Austin Tate & David Wilkins AIAI...

SUO/PDAARPI Fall 1999 Workshop 1

ARPIARPISmall Unit Operations SUO/PDA

Austin Tate & David WilkinsAIAI & SRI InternationalE-mail: [email protected], [email protected]: http://www.aiai.ed.ac.uk/~arpi/SUO/


ARPIARPISmall Unit Operations SUO/PDA

Advanced Planning Technology Schedule

SUO/PDA Objective

Demonstrate capability relevant to a SUO/Situation Assessment System (SAS) environment to generate, refine, select, communicate, execute and repair plans across multiple echelons.

Limited interfaces available on soldier-borne device.

Two examples of COA plan generation and use:- Defensive - Halt an Attack in Restrictive Terrain;- Offensive - Military Operations in Urban Terrain.

2QCY99 - SUO Scenario and storyboard/demo script development. Walk-through of technical requirements, mockup of non-working parts. Produce demo script and scenarios.

3QCY99 - Technology and demonstration development first pass, interim demonstration.

4QCY99 & Q1CY00 - Full demonstration development.

1Q & Q2CY00 - Transition and communication of results to SUO contractor. Refinement of demonstration and technology.

• Use results of DARPA/AFRL Planning Initiative (ARPI) and Planning & Decision Aids (PDA) work

• Multi-Agent Planning Architecture (MPA) and O-Plan Systems Integration Architecture

• SIPE-2/CPEF and O-Plan AI Planners• Mixed Initiative Planning Aids• Planning Domain Knowledge Acquisition Tools/Editors• Continuous Planning, Re-planning and Plan Repair• Planning Process Panels• Rich Shared Plan Representations


ARPIARPIObjective

• Demonstrate capability relevant to a SUO/Situation Assessment System (SAS) environment to generate, refine, communicate, execute and repair plans across multiple echelons.

• Limited interfaces available on soldier-borne device.

• Two examples of COA plan generation and use:

• Defensive - Halt an Attack in Restrictive Terrain;

• Offensive - Military Operations in Urban Terrain.


ARPIARPIApproach

• Use results of DARPA/AFRL Planning Initiative (ARPI) and Planning & Decision Aids (PDA) work

• Multi-Agent Planning Architecture (MPA) and O-Plan Systems Integration Architecture

• SIPE-2/CPEF and O-Plan AI Planners• Mixed Initiative Planning Aids• Planning Domain Knowledge Acquisition Tools/Editors• Continuous Planning, Re-planning and Plan Repair• Planning Process Panels• Rich Shared Plan Representations


ARPIARPILong-term Contributions to the Soldier

• Fast generation of multiple distinct COAs, including ones the commander may not have considered.

• Commander can explore more options in detail.

• Avoid mistakes: uniformly high plan quality, even during high-stress crises.

• Monitor plan execution and respond quickly to events, helping the commander modify the plan appropriately.

• Provide relevant information to other echelons, allowing fast communication while preserving bandwidth.


ARPIARPIPractical Issues/Challenges

• Effort to acquire the knowledge base (KB). • KB will cover a small subset of an officer’s knowledge and will add value.• Effort commensurate with capability.• Reduce effort by limiting scenario, relying on human knowledge, etc.• Human can override PDA -- blind spots not fatal• Other DARPA programs address this problem in the larger scale

• Assumptions about the world information available from sensors.

• Rely only on information which the SUO/SAS can provide• Baseline: SALUTE reports and GPS data.

• Input and output burden on soldiers when using SUO/PDA.• PDA would augment officer at time he would consult map or talk on radio• Voice input and limited interface modalities being considered by SUO contractor.

• Sensor planning• PDA will plan for awareness requirements• PDA will respond to reports from SAS• Will not model low-level details of sensor operations, or plan their exact deployment


ARPIARPI

• Validate MPA by integrating several systems in DARPA Planning Initiative (TIE 97-1):

INSPECT (ISI) OPIS (CMU) Advisable Planner (SRI)

SIPE-2 (SRI) ACS (UMass) Process Panel (AIAI -UEdin)

APAT (ISX) VISAGE (MAYA)

• Domain is Air Campaign Planning

• thousands of objects, several thousand nodes in each plan

• plan down to support mission level (must allocate supporting resources)

• air superiority objective only

• targets grouped into networks which depend on other networks

• network effectiveness is modeled quantitatively

Integration/TIEs


ARPIARPITIE 97-1 Demonstrations

• Sept 98 - EFX 98, Ft. Walton Beach FL

• May 98 - ARPI Workshop, Monterey CA

• Feb 98 - DARPA, Arlington VA

• Dec 97 - JFACC PMR, San Pedro CA

• Nov 97 - ARPI Workshop, San Francisco CA

Inc r

eas i

n g C

apab

ilit

ies

DARPADARPA


ARPIARPITechnology Transition

DARPA SUO program:

-prototype planning and decision aid

DARPA JFACC program:

-building on Cypress, MPA, TIE 97-1 MAPVis


ARPIARPISUO Scenarios

• Two SUO-SAS scenarios have been chosen:• Military Operations in Urban Terrain (MOUT):

Operation San Roberto

• Halt an Attack in Restrictive Terrain:

Operation Golden Manacle

• KA has been performed for both scenarios

• Interim demo is in MOUT scenario

• Main demo is in Halt an Attack scenario


ARPIARPIDifferences between the Two Scenarios

Halt an Attack Defensive Restrictive wooded terrain Battalion-sized operation Wide area move planning Mechanized threat Wide area sensors BN, CO, PLT Workstation-based aids Graphics+typing modalities

MOUT Offensive Close confined urban terrain Company-sized operation Close combat Foot soldier threat Localized sensors CO, PLT, SQ Soldier-borne aids Glance+select modalities


ARPIARPI

Opportunities for PDA Support in MOUTOpportunities for PDA Support in MOUT

Overall Process from Receipt of Mission to Success

Deliberative Planning & Rehearsal

En-route Rehearsal & Replanning

Low Tempo Adaptation & Plan Repair

High Tempo Monitoring & Plan Selection

After Action Planning &

Support

In Advance During Mission After Action


ARPIARPI

MOUT Concept of Operations

1st Plt

2nd Plt

OP “M” 3rd Plt 4th Plt


ARPIARPIHalt an Attack - Defensive Scenario

• Halt a mechanized enemy regiment in restrictive terrain with a SUO battalion

• Place obstacles to force enemy into engagement area

• Use forward infantry to observe, channel, and delay

• Rely on fire support to attrit

• Channel enemy to Southwest

• Use a CO(+) to defeat enemy in engagement area


ARPIARPIDefensive Scenario - Plan Generation

• BN plan/order is input to PDA

• PDA produces plans for each CO and each PLT

• KB covers following:• Observing avenues of approach (AAs)

• Using sensors to provide and supplement observation and to provide security

• Covering AAs with obstacles

• Positioning units

• Selecting a channelizing path for OPFOR

• Nominating positions for fire support (FS) units

• Selecting an engagement area (EA) in which to defeat channelized units

• Preparing the EA for the battle


ARPIARPIMain Demo - Halt an Attack

CompanyPlanning &Execution

System

OPORDFRAGO

PlatoonExecutionSupportSystem

OPORDFRAGO

BattalionPlanning &Execution

System

Reports

Reports

Domain ModelActivity

Templates &Constraints

Initial BattalionOPORD Creation

and Editing

Control PanelUser Interfaces& C2 ProcessManagement

World Simulationand Scenario

Event Generation

SUO/SAS System

World Simulator

AIAI Responsibility

SRI Responsibility


ARPIARPISUO/PDA Knowledge Acquisition Stage

Process ModellingMethods& Tools

Knowledge Acquisition for Halt an Attack(SRI with AIAI)

Army CALL BulletinsDoctrine, SOP, TTP

Subject Matter Experts

Domain ModelActivity

Templates &Constraints

SIPE Acts

O-Plan TF

SUO 3 Repn.Knowledge Acquisition for

MOUT(AIAI with SRI)

AIAI Responsibility

SRI Responsibility


ARPIARPIAIAI Contributing Technology

Austin Tatewith Jeff Dalton, John Levine, Peter JarvisAIAI, University of Edinburgh80 South Bridge, Edinburgh, UKE-mail: [email protected]: +44 (131) 650 2732

www:http://www.aiai.ed.ac.uk/project/oplan http://www.aiai.ed.ac.uk/project/ix



• Generation of multiple qualitatively distinct alternative COAs dependent upon alternative assumptions and advice about the situation.

• Support for mixed-initiative incremental plan development, manipulation and use.

• Situation-dependant plan repair as situation changes.

• Systems integration framework for modular planning and plan analysis systems.

• Management of planning and execution process - promotion of intelligent process management and workflow concepts.



• Shared Models of Tasks, Processes and Plans

• Issue-based Problem Solving

• Constraint and Domain Management

• Planning Process Panels

• Web Delivery of Planning Facilities

• Process Editor

• Previous O-Plan Technology

• New I-X Technology


ARPIARPI

Shared Plan Model - a rich plan representation using

a common constraint model of activity (<I-N-CA>).

Shared Task Model - Mixed initiative model of

“mutually constraining the space of behaviour”.

Shared Space of Options - explicit option management.

Shared Model of Agent Capabilities - handlers for

issues, functional capabilities and constraint managers.

Shared Understanding of Authority - management

of the authority to plan (to handle issues) and

act which may take into account options,

phases and levels.


ARPIARPIO-Plan -> I-X

InterfaceManager

ControllerProcessingPlatform(s)

Data Base Manager

Plan State Issues Nodes Constraints

ConstraintAssociator

Issue Handlers

Information Sources

Constraint ManagersPlanWorldViewers

RequirementsRequirements

Reports Reports

Constraint Managers

Processing Capabilities

Technical & World Viewers

Task & OptionManagement

ModelManagement

Mediators/MappingInformation Sources

RequirementsRequirements

Reports Reports


ARPIARPII-Plan and <I-N-CA>

Plan Agenda

Plan Entities

Plan Constraints

Plan State

Space of Legitimate Plan Elaborations

Choose (IH)

Do (IH)

IH=Issue Handler (Agent Functional Capability)

PropagateConstraints

Issues or ImpliedConstraints

NodeConstraints

DetailedConstraints

I

N

CA

C=Critical ConstraintsA=Auxiliary Constraints


ARPIARPISRI Contributing Technology

David Wilkins, Tom Lee SRI InternationalArtificial Intelligence CenterMenlo Park, CAE-mail: [email protected]: 650-859-2057

www: http://www.ai.sri.com/~sipe http://www.ai.sri.com/~cpef


ARPIARPI

Domain Characteristics

• Tasks are complex and open-ended

• Operating environments are dynamic and possibly hostile

• Complete and accurate knowledge of the world can never be attained

• Full automation is neither possible nor desirable Successful operation requires a mix of

• user involvement and control

• continuous planning

• rapid response to unexpected events

• dynamic adaptation of activities

Intelligent Operations Management


ARPIARPICPEF Architecture

Plan Manager

PRS

Planner

AP/SIPE

Simulator

PRS

Repair

Requests

Repair

Info

Plan

Requests

Plan Info

Situation

Updates

Execution

Status

Execution

Requests

Updates,

Guidance

Plan Server

PRS

Interface

PRS

Plan Repair

PRS

Notifications,

Requests

Plans

PlansPlans

MPA Messages

SUO/PDA ARPI Fall 1999 Workshop 1ARPI Small Unit Operations SUO/PDA Austin Tate & David Wilkins AIAI...

Documents

Transcript of SUO/PDA ARPI Fall 1999 Workshop 1ARPI Small Unit Operations SUO/PDA Austin Tate & David Wilkins AIAI...