27-April-19991 PST: A Distributed Real-Time Architecture for Physics-based Simulation and Hyper-Spectral Scene Generation Michael John Muuss U. S. Army.

27-April-1999 1

PST: A Distributed Real-Time Architecture for

Physics-based Simulation and Hyper-Spectral Scene Generation

Michael John MuussU. S. Army Research Laboratory

Maximo LorenzoU. S. Army CECOM

Multi-Spectral Scene Generation Workshop Redstone Technical Test Center

27-April-1999 2

Why We Model

• We are predicting or matching physical phenomena:+ Damage statistics of live-fire tests. + Energy levels received by a sensor.

• Hollywood storytellers communicate feelings to people. “Skin-deep” models are fine for them.

27-April-1999 3

Current & FutureChallenges for T&E

• In simulation, re-creating the real-world:+ Re-creating individual engineering tests.

• S&E community starts here.+ Re-creating real proving grounds.+ Re-creating training centers and training exercises.+ Re-creating combat locations and scenarios.

• Training community & wargamers start here.

27-April-1999 4

The Simulation Challenge

27-April-1999 5

Meeting the Simulation Challenge

• Engineering-level geometric detail.• Physics-based simulation.• Realistic 3-D atmosphere, ground, and sea models.• Fast: Real-time, near-real-time, Web, and offline.

+ Hardware-in-the-loop, man-in-the-loop.• Common geometry.• Common software.• Massively parallel processing.

27-April-1999 6

What is PST?

• PST = PTN and SWISS, Together!+ PTN = Paint-the-Night

• Real-time polygon rendering• From CECOM NVESD

+ SWISS = Synthetic Wide-band Imaging Spectra-photometer and Environmental Simulation• Ray-traced BRL-CAD™ CSG geometry• From ARL/SLAD

27-April-1999 7

Paint-the-Night

• 8-12 micron IR image generator.• SGI Performer based.• Uses outboard image processor for sensor effects.• A large highly tuned monolithic application

+ With exceptionally high performance.+ Highest polygon rates seen on a real application.

• Individually drawn trees (2 perpendicular polygons)• Individually drawn boulders.

27-April-1999 8

SWISS

• A physics-based synthetic wide-band imaging spectrophotometer+ A camera-like sensor + Looks at any frequency of energy.

• A set of physics-based virtual worlds for it to look at:+ Atmosphere, clouds, smoke, targets, trees,

vegetation, high-resolution terrain.• A dynamic world; everything moves & changes.

27-April-1999 9

Ray-Tracing Overview

27-April-1999 10

Advantages of a Ray-Tracing SIG

• Allows reflection, refraction:+ Windshields, glints.+ Branch reflections, 3-5.

• Atmospheric attenuation, scattering.+ Individual path integrals.

• Accurate shadows:+ Haze, clouds, smoke.

• Multiple light sources:+ Sunlight, flare, spotlight.

2nd-Generation FLIR image

(Downsampled to 1/4 NTSC)

27-April-1999 11

CSG Rendering Advantages

• Ray-traced CSG is free from limitations of hardware polygon rendering:+ No approximate polygonal geometry.

• No seams, exact curvatures.+ Exact profile edges. Important for ATR!+ No level-of-detail switching, no “popping”.+ Full temperature range in Kelvins, not 0-255.+ Unlimited spectral resolution, not just 3 channels.

27-April-1999 12

Cruise Missile Shadow

Ridge Profile

Missile Shadow

Terrain Quantization

27-April-1999 13

A Grand-ChallengeComputing Problem

• Real targets, enormous scene complexity, > 10Km2.• Physics-based hyper-spectral image generation.• Nano-atmospherics, smoke, and obscurants.• Ray-traced image generation, exact CSG geometry.

+ Near-real-time (6fps).• Fully scalable algorithms.• Network distributed MIMD parallel HPC.• Image delivery to desktop via ATM networks.

27-April-1999 14

Target Geometry Complexity

• Need at least 1cm resolvable features on targets.

27-April-1999 15

Complex Geometry Today

• < 1cm target features.• 1m terrain fence-post spacing• Three-dimensional trees:

+ Leaves.+ Bark.

• Procedural grass, other ground-cover.

• Boulders, other clutter.Current

Developmental

27-April-1999 16

One Geometry,Multiple Uses

• To compute ballistic penetration & vulnerability:+ Need 3-D solid geometry and material information.

• The same targets are also useful for:+ Signatures: Radar, MMW, IR, X-ray, etc.+ Smoke & Obscurants simulation.+ Chem./Bio agent infiltration.+ Electro-Magnetic Interference.

27-April-1999 17

Library of Existing BRL-CAD™ Geometry

27-April-1999 18

Ray-Traced Atmosphere

• Propagation easy in vacuum!

• Modeling four effects:

+ Absorption

+ Emission

+ In-scatter

+ Out-scatter

• Computer can’t do integrals.

+ Repeated summation

+ Discretized atmosphere

27-April-1999 19

The Blue Hills of Fort Hunter-Liggett

27-April-1999 20

Sources of Volumetric Atmospheric Data

• Need gas-density(x,y,z) for each gas species.• Sources:

+ Predictive: Nano-meteorology model.+ Re-enactment: input from measurements.

• E.g. Smoke-week data.+ Statistical: noise, FBM, fractals.

• Generates data with specified statistics.

27-April-1999 21

Hyper-Spectral: The Power of a Single Pixel

27-April-1999 22

Real-timeSpectral Analysis

27-April-1999 23

PST Implementation Goals

• To have a software backplane:+ Allowing each function to run as separate process.+ Allowing easy reconfiguration.+ Allowing independent software development.+ Using common geometry throughout.+ Multiple Synthetic Image Generator (SIG) types.

• Keep simulation details out of the SIGs.

27-April-1999 24

A Basic PST Simulation

PTN

SIG

Data-cube

DB

Solar

Load

Gen

Atmosphere

Ground Therm

Tree Therm

Target Therm

Monitor

MetTextures

Input

Transducers

Entity

ControllersWorld

Simulations

Sensor

Simulation Output

Transducers

ToD

MFS3

HW

FlyBox

Mapper

Mapper

MapperVehicle

Controller

Vehicle

Dynamics

MODSAF

I/F

Vehicle

Dynamics

Sensor

Controller

MODSAF

Intersect

Process

Magic

Carpet

27-April-1999 25

Independent Time Scales

• Image generators need to run fast:+ 30 Hz for humans.+ 6 Hz is fastest acquisition rate of ATRs.+ 800 Hz for non-imaging sensors (Stinger rosette).

• Physics-based simulations can run slower:+ 90 sec/update for thermal & atmosphere models.

• Transient effects need to be added as a delta:+ Leaf flutter, explosions, smoke details.

27-April-1999 26

Hardware Environment

• Multiple CPUs per cabinet.• Multiple cabinets linked via OC-3 or OC-12 ATM.

+ Geographically distributed (Belvoir, APG, Knox).• Multi-vendor system, e.g.:

+ Cray vector machine for thermal mesh solution.+ SGI Origin 2000 for parallel ray-tracing.+ SGI Infinite Reality for polygon rendering.

• 100-200 processors participating.

27-April-1999 27

V/L Server

Terrain

Thermal Models

VehicleDynamics

Paint-the-NightPolygon Renderer

BRL-CAD™Ray Tracer

::

HLA

with

enh

ance

men

ts

Backplane Philosophy

• Standardized Slots (Interface).• Location independent

+ Except for performance.

Paint-the-NightPolygon Renderer

27-April-1999 28

PST Implementation Plan

• Attempt to implement PST using HLA.+ Concern over real-time performance.+ No support for bulk data transfer.

• Fall back on JMASS, TARDEC, or home-brew.

27-April-1999 29

HLAFederation

Federate b

Federate c

Federate dFederate e

Federate f

Federate a

HLA FeaturesPublish and subscribe to objects and interactions

27-April-1999 30

Required Backplane Features

• Event Services+ Implement with HLA interactions.

• Query/Response Services+ HLA interactions with custom routing space.

• Continuous/Bulk Data+ Custom Distributed Shared Memory software.

• Auto-broadcast, optional subscriber notification.• Notification, subscriber polls for data update.

27-April-1999 31

HLA Ping

• Tool to measure communications delay.+ Patterned after Muuss’s TCP/IP ping tool.

• Special ping client federate.• Common ping server interaction in all federates.• Uses federate_id routing space for efficiency.• Measurements:

+ Round-trip (interaction pair).+ Half-trip (if both federates in same cabinet).

27-April-1999 32

RTIRTIRTIRTI

HLA Ping Diagram

Ping Client

Federate

Ping Client

Federate

Request Packet

Reply Packet

Ping Target

Federate

? ?

??

27-April-1999 33

PST FOM Basics

• ECEF coordinates, 64-bit IEEE double precision.• Using Quaternions to represent orientation.• Entity motion always sent in motion_t:

+ Position, velocity, acceleration,+ Orientation, Orientation dot, Orientation dot dot.+ Facilitates dead-reckoning in SIGs, simulations.

• Point-of-View interaction: motion_t & “handle” obj.+ Moving POV stays attached to moving entity.

27-April-1999 34

TerrainServer

Driver MGED

User

HLA Tcl / Tk

Tcl / Tk Tcl / Tk

VPG Demonstration

27-April-1999 35

Geometry Database

• A superset collection. Each entity will have:+ The original BRL-CADTM CSG model.+ Polygonal models at various LoD.+ Optical and thermal textures.+ Iconic representations: e.g. burning, destroyed.+ Nodal decomposition for input to thermal solvers.+ Articulation graph+ Definition of damage-state vector.

27-April-1999 36

Two HLA Wrappers

• Muuss strategy: Hide all HLA and XDR inside C++ “send” and “receive” methods. + One C++ object for each HLA interaction & object.+ Simulations need little HLA, C++ objects need lots.

• Baldwin strategy: Build total-insulation library.+ C++ objects know nothing about HLA.+ But XDR becomes very difficult.

27-April-1999 37

Working Testbed

Flybox

Mapper

SGI-Performer

Image Generator

Monitor

Vehicle

Dynamics

Controller

FlyBox

Ping Client

27-April-1999 38

Facilitating the“GOD GUI”

• We desire the ability to reach into a running simulation and “force” parameters.+ E.g. teleport a vehicle, heat some ground...

• Use HLA object ownership, or one multi-cast application-layer interaction?+ Object ownership uses 8+ network transmissions.

27-April-1999 39

Application of PST

• The image generator is just one component of a larger simulation. E.g. MFS3, or missile simulation.

PSTPST ATR6 DoF

Flight DynamicsImages

Motion_t

Full Environment SimulationFull Platform Simulation

or HWIL

Control Decisions

Full Platform Simulation

or HWIL

27-April-1999 40

Ft. Knox Applicationof PST

• 1 RT SIG, 3 SGI SIGs, soldiers-in-the-loop.

DTV

DTV

DTV

DTV

PSTPST

RT

PTN

PTN

PTN

DREN

ATM

AT

M to D

-2 Video

Digital V

ideo to AT

M

Mapper

Mapper

Mapper

Mapper

DREN ATM

27-April-1999 41

Who is this MUUSS Fellow, Anyway?

Mike Muuss

Señor Scientist

U.S. Army Research Laboratory

APG, MD 21005-5068 U.S.A.

<[email protected]>

http://ftp.arl.mil/~mike/