Tracking Moving Devices with the Cricket Location System - PowerPoint PPT Presentation

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  1. Tracking Moving Devices with the Cricket Location System Adam Smith, Hari Balakrishnan, Michel Goraczko, and Nissanka Priyantha Mobisys, 2004 Ku Dara

  2. Contents • Introduction • Tracking Algorithm • Hybrid Architecture • Evaluation • Conclusion Tracking Moving Devices with the Cricket Location System

  3. Human navigation Multi-player games Robotic navigation Introduction(1/4 ) • Location-aware application Direct users to their desired destinations on active map Lacation sensors provide position information to a moving robot Players can move in the real world game like Doom or Quake Tracking Moving Devices with the Cricket Location System

  4. Introduction(2/4) • Location-awareness system Indoor environment Outdoor environment Active Badge(infrared) GPS (Global Positioning System) Active Bat(ultrasonic) Hiball tracking system(infrared LED) Whisper system(audio) Cricket(RF,ultrasonic) Tracking Moving Devices with the Cricket Location System

  5. Introduction(3/4) • Indoor location architecture Infrastructure receivers Infrastructure trasmitters DB receiver trasmitter Cricket system Active Badge, Active Bat Tracking Moving Devices with the Cricket Location System

  6. Introduction(4/4) • Comparison • Active mobile architecture • Cost high, scalability low, performance high • Require a network infrastructure to connect the deployed receiver to central database • raising privacy concern • Passive mobile architecture • Scalability high, cost low, performance low • Independent privacy concern Tracking Moving Devices with the Cricket Location System

  7. Tracking algorithm(1/5) • Three Componets of tracking algorithm • Lesat-squares minimization(LSQ) • Use LSQ to reset the bad EKF state • Extended Kalman filter(EKF) • Predicte next device’s state from samples • Correct the prediction each time new distance sample is obtained • Outlier rejection • Bad distance sample eliminate [t,p,d] t:current time p:known position of the beacon or receiver d:distance btwn mobile device and known beacon or receiver Φ:a good positionestimate Tracking Moving Devices with the Cricket Location System

  8. di : B (||φ- pi|| - di) A-B error Current location estimateφ Reciever location pi ||φ- pi|| : A Tracking algorithm(2/5) • LSQ(Least Squares Minimization) • If mobile devices were static, a standard way to solve the problem of estimating is by minimizing the sum of the squares of the error terms corresponding to each distance sample • LSQ is complex • LSQ does not always produce a good estimate • Use to initializing and reseting the Kalman filter (bad state) A B Tracking Moving Devices with the Cricket Location System

  9. INPUT EKF OUTPUT [ ] samples estimate Φ T x , y , z , v , v , v x y z Internal state Tracking algorithm(3/5) • EKF(Extended Kalman Filter) • Using a state vector with six components • Three position components(x,y,z), three velocity components( ) • Use the most recent distance sample and internal state to project ahead and produce an estimate of Φ of where the device might be in the next time-step • P model: velocity and higher-order derivatives are zero • PV model: acceleration and higher order derivatives are zero • Multi-modal filter: combining the output states of PV and P models Tracking Moving Devices with the Cricket Location System

  10. Tracking algorithm(4/5) • Outlier Rejection • Wherein egregiously bad distance samples are eliminated Outlier Rejection bad samples outlier elliminated samples IF( ?) True→eliminate False→accept r : residual(guess-actual measurement) γ:empirically-selected parameter Tracking Moving Devices with the Cricket Location System

  11. Tracking algorithm(5/5) • Tracking algorithm Measurements t:current time p:known position of the beacon or receiver d:distance btwn mobile device and known beacon or receiver transmitter EKF next position extimate Current estimate distance correct Tracking Moving Devices with the Cricket Location System

  12. Hybrid Architecture(1/3) • Problem • Bad EKFstate • Extremely different estimate • Passive mobile system has a higher probability of reaching a bad state • Rarely happen in active mobile 1 2 3 1 2 3 [1][2][3] [1][2][3] [1][2][3] [1] [1][2] [1][2][3] Recent value Old value active mobile:multiple samples, accurate Passive mobile:one sample, inaccurate Tracking Moving Devices with the Cricket Location System

  13. Hybrid Architecture(2/3) • Solution • Normal state: passive mode use for Scalability, user-privacy • Bad Kalman filter state: active mode use Tracking Moving Devices with the Cricket Location System

  14. Hybrid Architecture(3/3) • Solution Compute distance samples RF message Beacon use a simple CSMA scheme with randomized back off to avoid RF collisions ActiveChirp receiver Reset EKF Internal state Tracking Moving Devices with the Cricket Location System

  15. Evaluation(1/4) • Experimental setup • Cricket’s h/w and s/w • Computer-controlled Lego train with Cricket attached to the moving train • Cricket listener to the train, beacons to the ceiling • Six different speed:model a range of realistic pedestrian speeds Tracking Moving Devices with the Cricket Location System

  16. Act 10cm P-LSQ 50cm Hv 20cm P-MM 30cm Evaluation(2/4) • Error CDF(speed:0.78m/s) • Passive • Multi-modal(MM) • 90%, error 30cm • LSQ • 90%,error 50cm (poor) • Precision MM>LSQ • Active • 90%, error 10 cm • High precision Occurrence error(cm) Tracking Moving Devices with the Cricket Location System

  17. Evaluation(3/4) • Error CDF(speed:1.43m/s) • Hybrid • 0.43 m/s: 90%, 20 cm • Speed increase, LSQ low precision High precision Active-MultiModal Hybrid-EKF-PV Passive-MultiModal Passive-LSQ Low precision Act 10cm P-LSQ 85cm Hv 45cm P-MM 65cm Tracking Moving Devices with the Cricket Location System

  18. Evaluation(4/4) • Median error • Hybrid close to active mode Passive 25cm below Hybrid 15cm below Active 5cm below Tracking Moving Devices with the Cricket Location System

  19. Conclusion(1/1) • Hybrid architecture • Preserve the scalability and privacy advantages of the passive mobile • Improving tracking precision Tracking Moving Devices with the Cricket Location System