Robotic Path Following using Navigational Unattended Ground Sensors (NAV-UGS)
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Robotic Path Following using Navigational Unattended Ground Sensors (NAV-UGS) A Work in Process Report. 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)

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Robotic Path Following using Navigational Unattended Ground Sensors (NAV-UGS)A Work in Process Report

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 Vehicles Systems Symposium

Grand Traverse Resort and Spa

Traverse City (Acme), MI

June 12, 2003


Agenda
Agenda Sensors (NAV-UGS)

  • Participants

  • Theory of operation/benefits

  • Simulation parameters and results

  • Experimental setup

  • Preliminary experimental results

  • Test plan


Participants
Participants Sensors (NAV-UGS)


Theory of operation benefits
Theory of Operation/Benefits Sensors (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

RF timing and sequencing

NAV-UGS

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

  • 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

Path marker or follower


How nav ugs path following works
How NAV-UGS Path Following Works Sensors (NAV-UGS)

  • 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.


Simulation runs parameters and assumptions
Simulation Runs—Parameters and Assumptions Sensors (NAV-UGS)

Vehicle

N

X

X

X

(60,Y0+Nd)

(60,Y0+d)

(60, Y0)

y

NAV-UGS

x

  • 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


Simulation runs results for constant 500 m spacing between nav ugs
Simulation Runs—Results for constant 500 m spacing between NAV-UGS

Ranging accuracy = 20 cm

Ranging accuracy = 50 cm

90 m Comms Range

90 m Comms Range

INS only

Meets requirement

INS + VMS

Path Error (m)

INS + VMS + NAV-UGS

0.5 m allowable path error

200 m Comms Range

200 m Comms Range

Better than requirement

Path Error (m)


Technology demo objectives
Technology Demo Objectives NAV-UGS

  • 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


Comparison of tech demo and objective solutions
Comparison of Tech Demo and Objective Solutions NAV-UGS

Parameter

Tech Demo

Objective

NAV-UGS

RF/acoustic hybrid

RF tag embedded in UGS

Follower Vehicle

Surrogate MGV with human driver acting as robotic controller

UGV follower

Number of Vehicles

One; marker/follower are same. Recycle INS power to simulate follower.

Unlimited; many markers and followers possible.

Speed/ Separation

55 kph / 3 km

65 kph / > 200 km

12 cm

Interim hybrid RF/ acoustic transmitter

Objective RF Tag

1 cm x 2.5 cm


Tech demo software design
Tech Demo Software Design NAV-UGS

SensoriaNAV-UGS

Velocity Est. Bearing& Range

SystemController

Mode(marker | follower)

OperatorDisplay &Controls

Start, Stop

Range

Driver Guidance

Setup Data

HoneywellTALIN INS

  • 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

Position, Velocity & Attitude

FollowerPath

INS/NAV-UGS Data,Path Definition

FollowerAlgorithm


Physical configuration
Physical Configuration NAV-UGS

Speedometer cable between transmission & VMS

DGPS scoring system antenna & receiver

Microphones and windscreens (4)

Driver’s display

M1037 HMMWV

Laptop NAV PC

Vehicle Motion Sensor (VMS)

Honeywell TALINTM INS

Sensoria RF antenna & Gateway

Power distribution electronics


3 km test course
3 km Test Course NAV-UGS

500 m

Start/ End

  • 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


Driver s virtual environment and display
Driver’s Virtual Environment and Display NAV-UGS

Driver’s compartment enclosed in blackout cloth

Laptop NAV computer

Speed indicator (and set point)

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

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


Virtual environment and display approach
Virtual Environment and Display Approach NAV-UGS

  • 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



Path follower scoring procedure for dynamic testing
Path Follower Scoring Procedure for Dynamic Testing play)

  • 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


Preliminary results nav ugs static ranging precision
Preliminary Results: NAV-UGS Static Ranging Precision* play)

0.5 m allowable path error

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

20

*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

Ranging accuracy = 20 cm

90 m Comms Range

Measured precision is sufficient to maintain vehicle paths within 0.5 m

Meets requirement


Preliminary results nav ugs static and dynamic ranging precision
Preliminary Results: NAV-UGS Static and Dynamic Ranging Precision*

Static

Dynamic

*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 kph


Test plan
Test Plan Precision*

  • 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


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