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Efficient RFID-Based Mobile Object Localization

Efficient RFID-Based Mobile Object Localization. Kirti Chawla , Gabriel Robins, and Liuyi Zhang Department of Computer Science University of Virginia, Charlottesville, USA {kirti, robins, lz3m}@virginia.edu.

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Efficient RFID-Based Mobile Object Localization

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  1. Efficient RFID-Based Mobile Object Localization Kirti Chawla, Gabriel Robins, and Liuyi Zhang Department of Computer Science University of Virginia, Charlottesville, USA {kirti, robins, lz3m}@virginia.edu This work is supported by U.S. National Science Foundation (NSF) grant: CNS-0716635 (PI: Professor Gabriel Robins) For more details, visit: www.cs.virginia.edu/robins

  2. Novel Application Scenarios Overview RFID Localization Pervasive Media Activity Recognition Elderly Care Real-time Tracking

  3. RFID Localization RFID-based Object Localization Overview Reader Localization Tag Localization Stationary Reader Localization Tag Reader Localization Mobile Reader Localization Mobile Tag Localization

  4. Localization Challenges Overview RF Interference Tag Sensitivity Tag Orientation Tag Spatiality Reader Locality Occlusions

  5. Underlying Principle Proposed Approach Reader Power Distance Tag Power

  6. Intersection of Detectability Regions Basic Approach Proposed Approach Localization phase Calibration phase

  7. Multi-Tag Platform Multi-Tag Calibration Proposed Approach Calibration under Rotation Calibration under Proximity Platform Design

  8. Linear Search for Tags Tag Localization Algorithms: Algorithm I Proposed Approach Start For each Tag Linear search for optimal tag detection power level Current Power Level > Threshold ? NO YES NO Optimal Power Level FOUND ? YES Report Optimal Power Level Stop Time = O(# tags  power levels)

  9. Binary Search for Tags Tag Localization Algorithms: Algorithm II Proposed Approach Start For each Tag Binary search for optimal tag detection power level Current Power Level > Threshold ? NO YES NO Optimal Power Level FOUND ? YES Report Optimal Power Level Stop Time = O(# tags  log(power levels))

  10. Parallel Search for Tags Tag Localization Algorithms: Algorithm III Proposed Approach Start Initialize power level of all tags to maximum Linearly decrement power level for all tags Power level = 0 ? NO YES NO Power level of a tag “fixed” ? YES Tag has optimal power level Stop Time = O(power levels)

  11. Measure and Report Reader Localization Algorithm Proposed Approach Start Tag Found ? YES NO Return “Not Found” Return Tag-IDand Timestamp Stop Time = O(1)

  12. Localization Error Proposed Approach Error Reference Tag Target Tag

  13. Heuristics: Absolute Difference Proposed Approach Error Reduction Heuristics: Heuristic I

  14. Heuristics: Minimum Power Reader Selection Proposed Approach Error Reduction Heuristics: Heuristic II

  15. Heuristics: Root Sum Square Absolute Difference Proposed Approach Error Reduction Heuristics: Heuristic III

  16. Error Reduction Heuristics: Meta-Heuristic Proposed Approach Heuristics: Absolute Difference Heuristics: Minimum Power Reader Selection Meta-Heuristic: Overall Minimum Localization Error Heuristics: Root Sum Square Absolute Difference Other Novel Heuristics

  17. Mobile Robot Design Track Design Experimental Setup Results 4 X-axis 1 3 2 Y-axis

  18. Constant Distance/Variable Power Results Multi-Tag Calibration – Proximity Sensitivity Invariant Variable Distance/Constant Power

  19. Constant Distance/Variable Power Results Multi-Tag Calibration – Rotation Sensitivity Invariant-B

  20. Variable Distance/Constant Power Results Multi-Tag Calibration – Rotation Sensitivity Invariant-A

  21. Localization Accuracy Localization Accuracy and Speed Results Localization Speed

  22. Accuracy vs. Tag Density Results Impact on Localization Accuracy due to Tag Density and Power-Step Size Diminishing returns Accuracy vs. Power-Step Size

  23. Results Comparative Analysis

  24. Results Localization Visualization Heuristics Work Area Accuracy Antenna Control

  25. Open Research Problems Future Directions Tag Spatiality Impact on Localization Accuracy and Speed Simultaneous Multiple Object Localization Activity Recognition Novel Applications

  26. Questions ?

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