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

1. 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

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

3. Participants

4. Theory of Operation/Benefits • 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

5. How 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.

6. Simulation Runs—Parameters and Assumptions 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

7. 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)

8. Technology 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

9. Comparison of Tech Demo and Objective Solutions 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

10. Tech Demo Software Design 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

11. Physical Configuration 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

12. 3 km Test Course 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

13. Driver’s Virtual Environment and Display 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

14. Virtual Environment and Display Approach • 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

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

16. Path Follower Scoring Procedure for Dynamic 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

17. Preliminary Results: NAV-UGS Static Ranging Precision* 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

18. 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

19. Test 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