NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 1

Robotic Path Following using Navigational Robotic Path Following using Navigational Unattended Ground Sensors (NAV-UGS)Unattended Ground Sensors (NAV-UGS)

A Work in Process ReportA Work in Process Report

Robotic Path Following using Navigational Robotic Path Following using Navigational Unattended Ground Sensors (NAV-UGS)Unattended Ground Sensors (NAV-UGS)

A Work in Process ReportA Work in Process Report

NDIA 3rd Annual Intelligent Vehicles Systems SymposiumGrand Traverse Resort and Spa

Traverse City (Acme), MI

June 12, 2003

Anthony J. Giovanetti, Albert Shyu and Lou McTamaney (UDLP)David Baughman (Honeywell)

Philip Frederick (U.S. Army TARDEC)William Merrill and Guillaume Rava (Sensoria Corporation)

Kris Alluri (SEI)

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 2

AgendaAgendaAgendaAgenda

Participants Theory of operation/benefits Simulation parameters and results Experimental setup Preliminary experimental results Test plan

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 3

ParticipantsParticipantsParticipantsParticipants

Company/Agency Capabilities Responsibilities

Combat vehicle development and integration

System development, integration, and test

Driver’s display development

Defense & Space Electronic Systems

High-accuracy inertial navigation systems for ground vehicles

TALINTM 4000 INS and navigation algorithm and error analysis

Robotics and unmanned vehicles

HMMWV manned surrogate platform

Wireless embedded systems and networking technology

Hybrid acoustic and RF ranging system

Software design, code and unit test

Software partitioning

Navigation computer software

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 4

Theory of Operation/BenefitsTheory of Operation/BenefitsTheory of Operation/BenefitsTheory of Operation/Benefits

RF timing and sequencing

NAV-UGS

What is it and what are its benefits?

An alternative to vision- or GPS-based path followers for unmanned vehicles

A driving aid for manned vehicles

High precision path following is possible, i.e., 0.5 m, 3dRMS

Works in confined quarters urban ops

Does not congest RF spectrum and less susceptible to jamming

Works with legacy systems

Adapts to FCS UGS

Marker/follower do not have to be on path at same time

What is it and what are its benefits?

An alternative to vision- or GPS-based path followers for unmanned vehicles

A driving aid for manned vehicles

High precision path following is possible, i.e., 0.5 m, 3dRMS

Works in confined quarters urban ops

Does not congest RF spectrum and less susceptible to jamming

Works with legacy systems

Adapts to FCS UGS

Marker/follower do not have to be on path at same time

Path marker or follower

What does it use and how does it work?

Uses a path marking vehicle, precision INS, and ground-based sensors (NAV-UGS)

Marker vehicle places NAV-UGS along path and encodes each with time/position coordinates derived from the ranging algorithm in terms of marker’s INS reference frame. May also encode terrain data.

Follower vehicles interrogate NAV-UGS and use encoded data to eliminate their accumulated INS errors to closely steer the marker’s path

What does it use and how does it work?

Uses a path marking vehicle, precision INS, and ground-based sensors (NAV-UGS)

Marker vehicle places NAV-UGS along path and encodes each with time/position coordinates derived from the ranging algorithm in terms of marker’s INS reference frame. May also encode terrain data.

Follower vehicles interrogate NAV-UGS and use encoded data to eliminate their accumulated INS errors to closely steer the marker’s path

High-accuracy acoustic ranging (1dRMS = 10 cm)

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 5

How NAV-UGS Path Following WorksHow NAV-UGS Path Following WorksHow NAV-UGS Path Following WorksHow NAV-UGS Path Following Works

Marker vehicle dispenses NAV-UGS when INS drift error exceeds 0.5 m.

Marker triangulates its position with respect to NAV-UGS using transceiver.

Marker encodes NAV-UGS position with respect to its location into NAV-UGS RAM. May encode other information, including terrain data.

Follower detects NAV-UGS, triangulates NAV-UGS location and compares this location to that stored by marker in RAM.

Follower uses difference in NAV-UGS location measurements to synchronize INS and steer closer to marker’s path.

Destination

Triangulation Calculation

x2, y2)x2*, y2*)

Triangulation Calculation

x1, y1)x1*, y1*)

N

W EStart (x0, y0)

S

Leader's path and waypointFollower's path and waypointCorrected follower path after reading NAV-UGS to update INSNAV-UGS

Max allowable Path Deviation = 0.5 m

Path segment assigned to

NAV-UGS #1

#1

#2

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 6

Simulation Runs—Parameters and Simulation Runs—Parameters and AssumptionsAssumptionsSimulation Runs—Parameters and Simulation Runs—Parameters and AssumptionsAssumptions

Simulates navigation error only; no vehicle control error Vehicle travels 55 kph constant speed due north Equally spaced NAV-UGS with 60-m cross track offset TALINTM 4000 INS with 0.25% accuracy per distance

traveled, vehicle motion sensor (VMS) aiding, but no GPS Vehicle communicates with one NAV-UGS at a time One valid measurement/sec per NAV-UGS

N

X X(60,Y0+d)

NAV-UGS

Vehicle

(60, Y0)y

x

X(60,Y0+Nd)

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 7

Simulation Runs—Results for constant Simulation Runs—Results for constant 500 m spacing between NAV-UGS500 m spacing between NAV-UGSSimulation Runs—Results for constant Simulation Runs—Results for constant 500 m spacing between NAV-UGS500 m spacing between NAV-UGS

90 m Comms RangeINS only

INS + VMS

INS + VMS + NAV-UGS

0.5 m allowable path error

Meets requirement

Better than requirement

Ranging accuracy = 50 cm Ranging accuracy = 20 cm

Path Error (m)

Path Error (m)

90 m Comms Range

200 m Comms Range 200 m Comms Range

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 8

Technology Demo ObjectivesTechnology Demo ObjectivesTechnology Demo ObjectivesTechnology Demo Objectives

Demonstrate INS aiding using ground-based navigation beacons

► Objective NAV-UGS will use miniature, developmental RF tag that provides high accuracy clock, narrow pulsewidth, and high bandwidth for cm-accuracy ranging over short distances

► For interim, use hybrid RF/acoustic COTS ranging system from Sensoria Corporation*

Show accurate path marking and following at 55 kph over a 3-km-long urban course

*Corrected for Doppler effects

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 9

Comparison of Tech Demo and Comparison of Tech Demo and Objective SolutionsObjective SolutionsComparison of Tech Demo and Comparison of Tech Demo and Objective SolutionsObjective Solutions

Objective RF Tag

Interim hybrid RF/ acoustic

transmitter

Parameter

NAV-UGS

Follower Vehicle

Number of Vehicles

Speed/ Separation

Tech Demo

RF/acoustic hybrid

Surrogate MGV with human driver acting as

robotic controller

One; marker/follower are same. Recycle INS

power to simulate follower.

55 kph / 3 km

Objective

RF tag embedded in UGS

UGV follower

Unlimited; many markers and followers possible.

65 kph / > 200 km

12 cm

1 cm x 2.5 cm

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 10

Tech Demo Software Design Tech Demo Software Design Tech Demo Software Design Tech Demo Software Design

SensoriaNAV-UGS

HoneywellTALIN INS

OperatorDisplay &Controls

SystemController

FollowerAlgorithm

Range

Velocity Est. Bearing& Range

Setup Data

Position, Velocity & Attitude

Mode(marker | follower)

Driver Guidance

FollowerPath

INS/NAV-UGS Data,Path Definition

Start, Stop

Marker Mode Algorithm Reads INS/NAV-UGS data Computes/records path segment data Upon reaching destination, computes

polynomial curve for all path segments

Follower Mode Algorithm Receives path definition Reads INS/NAV-UGS data Computes cross track & velocity

errors Displays errors to driver in user

friendly format

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 11

Physical ConfigurationPhysical ConfigurationPhysical ConfigurationPhysical Configuration

Vehicle Motion Sensor (VMS)

Speedometer cable between transmission & VMS

Honeywell TALINTM INS

Microphones and windscreens (4)

DGPS scoring system antenna & receiver

Sensoria RF antenna & Gateway Power distribution

electronics

Laptop NAV PC

Driver’s display

M1037 HMMWV

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Start/ End

3 km Test Course3 km Test Course3 km Test Course3 km Test Course

Urban environment with sharp turns and abandoned buildings Includes overhead obstructions that block GPS signal Minimum/maximum path speeds = 16/55 kph Deploy NAV-UGS every 100 m

500 m

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 13

Driver’s Virtual Environment and Driver’s Virtual Environment and DisplayDisplayDriver’s Virtual Environment and Driver’s Virtual Environment and DisplayDisplay

Heading indicator & turn coordinators (plan and out-the-window views)

Laptop NAV computer

Human driver serves as robotic controller maintaining Human driver serves as robotic controller maintaining vehicle heading and speed using only display vehicle heading and speed using only display commands and without reference to horizoncommands and without reference to horizon

Speed indicator (and set point)

Driver’s compartment enclosed in blackout cloth

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 14

Virtual Environment and Display Virtual Environment and Display ApproachApproachVirtual Environment and Display Virtual Environment and Display ApproachApproach

UDLP real-time Interactive Vehicle Model (IVM) simulates dynamics

► Six DOF for vehicle chassis—3 translational and 3 rotational► One DOF for each wheel—translation perpendicular to chassis► Suspension spring and damping► Tire-to-ground spring and damping ► Propulsion system forcing function uses throttle, brake, and steer

inputs; outputs engine and wheel speeds

Control algorithm uses Matlab Simulink► Generates speed (throttle, brake) and steer commands for driver

to follow prescribed path

IVM displays vehicle track in two formats: out-the-window and plan view

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 15

Virtual Environment Demonstration Virtual Environment Demonstration (.avi file—click to play)(.avi file—click to play)Virtual Environment Demonstration Virtual Environment Demonstration (.avi file—click to play)(.avi file—click to play)

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 16

Path Follower Scoring Procedure for Path Follower Scoring Procedure for Dynamic TestingDynamic TestingPath Follower Scoring Procedure for Path Follower Scoring Procedure for Dynamic TestingDynamic Testing

Use COTs NovAtel DGPS surveying system to precisely locate each NAV-UGS position on the test course (expected static accuracy + 2 cm true position)

Synchronize navigation system time to scoring system GPS time (1 ms time difference ~ 2 cm position error)

Calculate NAV-UGS measurement error► Calculate true range from surveyed NAV-UGS locations and true trajectory► Subtract true range from NAV-UGS computed range► Post process DGPS data to obtain vehicle true dynamic position (expected

accuracy within +4 cm true position) Isolate NAV-UGS measurement error from NAV algorithm

► Rerun navigation algorithm using recorded INS data and true range measurements

Isolate guidance and control errors► Calculate NAV algorithm position estimates based on NAV-UGS locations,

segment path distance and downtrack/crosstrack errors► Subtract NAV algorithm estimated position from true positions to find

guidance and control errors

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Preliminary Results: NAV-UGS Static Preliminary Results: NAV-UGS Static Ranging Precision*Ranging Precision*Preliminary Results: NAV-UGS Static Preliminary Results: NAV-UGS Static Ranging Precision*Ranging Precision*Nominal range to

NAV-UGS (m)Number of samples

1 dRMS error (cm)

R90 (cm)**

55 9 6.3 10

61 8 8.3 13

91 19 12.4*Outdoors with 5 kt winds; NAV-UGS on ground; microphones 1 m above ground; distance to NAV-UGS measured with tape and then compared to acoustically-derived range

**90% of all events

Measured precision is Measured precision is sufficient to maintain sufficient to maintain

vehicle paths within 0.5 mvehicle paths within 0.5 m

Meets requirement

Ranging accuracy = 20 cm

90 m Comms Range

0.5 m allowable path error

20

NDIA 3rd Annual Intelligent Vehicle Systems Symposium, June 9 - 12, 2003 18

Preliminary Results: NAV-UGS Static Preliminary Results: NAV-UGS Static and Dynamic Ranging Precision*and Dynamic Ranging Precision*Preliminary Results: NAV-UGS Static Preliminary Results: NAV-UGS Static and Dynamic Ranging Precision*and Dynamic Ranging Precision*

Nominal Range to

NAV-UGS (m)

Number of

samples

1 dRMS error (cm)

R 90

(cm)**

55 9 6.3 1061 8 8.3 1391 19 12.4 20

19.4 10 8.5 1417.3 12 2.6 411.6 6 3.5 6

16 13.9 3 2.1 325 19.0 3 2.1 335 15.8 2 9.1 15

Speed (kph)

0

5

*Doppler corrected**90% of all events. Dynamic dispersion

computed about INS predicted position, corrected for any initial offset error in locating NAV-UGS in INS coordinates.

Measured precision is within 20 cm up to 35 kphMeasured precision is within 20 cm up to 35 kph

NAV-UGS Range Error

0

5

10

15

20

25

0 50 100

Nominal Range (m)R

90 (

cm

)

DynamicDynamic

StaticStatic

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Test PlanTest PlanTest PlanTest Plan

Prepare the test course► Use NAV simulation to plan path and locate NAV-UGS► Survey NAV-UGS locations onto course using DGPS

Perform marker vehicle tests over 3 km course► Collect data from NAV-UGS and INS at prescribed speeds► Post process data to generate coefficients for path polynomials

Demonstrate precision path following over 3 km course► Train driver to follow heading and speed commands without reference to

horizon► Drive path using data from INS, NAV-UGS, and NAV algorithm

Compare results to DGPS scoring system to demonstrate follower tracks within + 0.5 m of marker’s path

Perform follower tests using INS + VMS aiding only and compare to INS + VMS + NAV-UGS aiding