-PIRATLA ADITYA

INDUSTRIAL POWER & AUTOMATIONDEPARTMENT OF ELICTRICAL ENGINEERING

NIT CALICUT

vINTRODUCTION.

vMOBILITY.

vLOCALIZATION.

vNAVIGATION.

CONTENTSCONTENTS

vNAVIGATION.

vCOMMUNICATION.

vPLANNING.

vINTERFACES.

vAPPLICATIONS.

vARMED UGV.

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INTRODUCTIONINTRODUCTION

vUGV: UNMANNED GROUND VEHICLESv Durrant-Whyte(2001) divided UGV technology into ‘5’

categories(1):

1. Localization.2. Mobility.3. Navigation.4. Planning.5. Communication.

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PLANNING

COMMUNICATION

LOCALIZATION NAVIGATION

Prior Map, goals,values

External sensors

Internal External

environmental sensors

MOBILITY

LOCALIZATION NAVIGATION

Vehicle

Internal sensors sensors

FIG1:Relationships Between components of UGV(Durrant-whyte) (1)42/17/2011

• Definition :methods through which robot updates or calculates position.(2)

LOCALIZATIONLOCALIZATION

Localization

Absolute Relative Absolute Relative

Landmark navigation

Map matching

Inertial navigation

Odometry

TOF active ranging

Active beacons

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vOptical absolute shaft ENCODER used in ODOMETRY

v81000 pulses per revolution.v 0.01µm resolution.

v GRAY CODE.

vRelative Localization: Onboard sensors like Encoders, Gyroscopes, accelerometers are used.

(3)

tpub.com

vRATE GYRO (4),(5) used in INERTIAL NAVIGATION.

vConservation of ANGULAR MOMENTUM.

vGyro fixed to vehicle frame.

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v Rotation along input axis resisted.

v Precession calibrated foroutput.

tpub.com

Pulse counting ccelerometers

vACCELEROMETERS (4),(5) used foracceleration measurement.

v Newton’s 2nd law of motion.vRELATIVE LOCALIZATION sensors

Use integration to compute position.

tpub.com

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vDRIFT in measured data.vShort durations.

vAbsolute Localization (2): Done using beacons, landmarks or maps.

vNo integration for Localization.

vActive Beacons like satellite send signals.vTriangulation & trilateration 2 commonly used

beacon techniques.vExcept location of beacon no a-priori information

required.

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vAccuracy of GPS about 1-4m.vAtmospheric & Geographic disturbance may influence signal

transmission.vAbsence of signal.v Active Beacons are Costly.

vLandmarks are fixed objects, either natural or artificial.vSonar, infrared sensing & vision sensing.vVehicle can be preloaded with landmark information.vOr may use self learning tools.

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vNoise & uncertainty in sensor reading.vOptimal use of sensed data critical.vProbabilistic BAYESIAN ESTIMATION (6) can be used

to account for uncertainty.vBayesian estimation characterized by BELIEF.vMarkov environment assumed.vHigh dimensional sensor

reading mapped to lower dimension.

vPrior & Posterior belief.10

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vMap Matching Positioning.vGlobal map matched with local maps.vMainly used in indoor mapping.

vTOF active ranging.vTOF active ranging.vUltrasonic, RF, Optical energy sources used.vLinear operation.vAccurate as long reliable echo obtained.

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vMobility (7) deals with vehicles mechanical design.

vNATO Reference Mobility Model (NRMM).vBecker Mobility Model

MOBILITYMOBILITY

vBecker Mobility ModelvMotion control technique.vVehicle-Terrain interaction.vAnalysis through principle of conservation of

energy.

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NAVIGATIONNAVIGATION

cognitionlocalization

Prior knowledge

Operator commands

Motion control

ugv

perception

Navigation control loop(2)132/17/2011

vNavigation(8)uses environment map from Localization.

vMotion strategy.vAccuracy should be in tune with vehicle

dimensions.

NAVIGATION

14

NAVIGATION

PERSONALLOCALGLOBAL

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vWireless Communication.vMulti Path Fading.vReal Time Data Transfer.

COMMUNICATIONCOMMUNICATION

vReal Time Data Transfer.vData Compression.v>10 Kbps BW.

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vAd Hoc Networking(9):i. Mobility.ii. Self Organizing.iii. Multi Hooping.iv. Energy Conservation.v. Scalability.

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vi. Security.vii. Connection to the internet.

a) Hybrid Wireless Networksb) Opportunistically

extendable networks.

vInput from all other blocks and Peripherals.

vGlobal Path Planning(10).

PLANNINGPLANNING

vGlobal Path Planning(10).vMotion Planning.vNon-holonomic Path Planning.vKino-dynamic Path Planning.

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vOutdoor Planning.vIndoor Planning.vAttributes of Planning:

a) Search space.b) Configuration space.c) Actions.

vCell decomposition.2/17/2011 18

c) Actions.d) Time.e) Initial state, Goal state.f) Constraints.g) Criteria.h) Algorithm.

APPLICATIONSAPPLICATIONSvIN EXPLORATION OF INHOSPITABLE TERRITORY.

vAUTOMATED TRANSPORTATION.

vDEFENSE PURPOSE. 192/17/2011

REFERENCESREFERENCES

1. Thanh Hung Tran P.H.D thesis on modeling and control of unmanned

ground vehicles, Sep-2007.2. Dr. Georgios A. Demetriou , A Survey of Sensors for Localization of

Unmanned Ground Vehicles (UGVs).3. Wikipedia.org.

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4. Integrated Publishing, tpub.com.5. Measurement Systems, Ernest O Doebelin, McGraw Hill international

edition.6. Sebastian Thrun, Bayesian Landmark Learning for Mobile Robot

Localization. 1997.7. HyukChul Nho, Jonathan Salton, Barry Spletzer, Scott Horschel, Mobility

Analysis of Robotic Ground Vehicles Based on Energy Method.

8. Jonathan Dixon, Oliver Henlich, final report, Mobile Robot Navigation1997

9. Ad Hoc Networks Technologies and Protocols, Edited by PrasantMohapatra University of California‚ Davis Srikanth V. KrishnamurthyUniversity of California‚ Riverside.

10. J. Giesbrecht, Defence R&D Canada – SuffieldGlobal Path Planning for Unmanned Ground Vehicles.

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-THANK YOU-THANK YOU

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