Object Localization Using RFID Kirti Chawla Department of Computer Science University of Virginia Outline • • • • • • • The Problem of Locating Objects Research Milestones Background Motivation Proposed Approach Experimental Evaluation Conclusion 1/23 Problem Locating Objects Locate Objects Environments Goal: Find positions of objects in an environment Hypothesis: Standard RFID is sufficient and effective Key-factors: Performance, applicability and shortcomings 2/23 Milestones Research Deliverables Journal Publication: • Kirti Chawla, and Gabriel Robins, An RFID-Based Object Localization Framework, International Journal of Radio Frequency Identification Technology and Applications, Inderscience Publishers, 2011, Vol. 3, Nos. 1/2, pp. 2-30 Conference Publications: • • Kirti Chawla, Gabriel Robins, and Liuyi Zhang, Efficient RFID-Based Mobile Object Localization, Proceedings of IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, 2010, Canada, pp. 683-690 Kirti Chawla, Gabriel Robins, and Liuyi Zhang, Object Localization using RFID, Proceedings of IEEE International Symposium on Wireless Pervasive Computing, 2010, Italy, pp. 301-306 Patent: • Kirti Chawla, and Gabriel Robins, Object Localization with RFID Infrastructure, US Patent Application Number: PCT/US2011/053067, filed with WIPO/USPTO September 2011 Copyright: • Kirti Chawla, and Gabriel Robins, An RFID-Based Object Localization Framework, US Copyright Case Number: 1-633487801, 2011 Startup Venture: • • • Co-founded Diorama Technologies LLC, in partnership with private investors Raised venture capital funding and negotiated licensing terms Other investors have shown strong interest in commercializing our ideas Patent WIPO/USPTO Object Localization with RFID Infrastructure Background Current State of the Art Mismatched Solutions Technologies Techniques Limiting Constraints 3/23 Background RFID Primer RFID Reader RFID Tag Far-field Propagation Near-field Propagation Readers: Variety of form-factors and frequencies Tags: Flexible power source, frequency, and form factors 4/23 Motivation Why locate objects using RFID ? Dark Environment No Line of Sight Cost Effective Solid Obstacles Natural Fit Adaptive 5/23 Approach Power-Distance Relationship Comparison N Tag Power Wavelength Tag Gain ×Reader Gain × Reader Power 4× π ×Distance Reader Power Distance Tag Power Problem: Radio variability renders Friis equation practically useless Insight: Utilize empirical power-distance relationship 6/23 Approach Empirical Power-Distance Relationship Antenna Shared Region Radio Wave Insight: Similarly behaving tags are close to each other 7/23 Approach Tag Sensitivity Characterization Results Key Challenges 13% Pile of Tags 25% 54% 8% High Sensitive Average Sensitive Low Sensitive Problem: Tags have variable sensitivities / performance Insight: Bin tags based on their sensitivity 8/23 Approach Reliability through Multi-Tags Results Vertical Parallel RFID Reader Platform Side View Horizontal Orthogonal Platform RFIDTop TagView Problem: Optimal tag reads occur at certain orientations Insight: Multi-tags provide orientation redundancy 9/23 Approach Tag Localization Approach Signal Strength Metric: MTDP Localization Phase Setup Phase 10/23 Approach 0 Tag Localization Algorithms MID MAX Reader Output Power Range Linear Search Binary Search Parallel Search O(#Tags #Power-Levels) O(#Tags Log#Power-Levels) O(#Power-Levels) 11/23 Approach Reader Localization Approach Localization Phase Setup Phase 12/23 Approach Localization Error Heuristics Reference Tags Target Tag Problem: Assumption that target and reference tag locations coincide leads to localization error Insight: Consider other nearby reference tags in order to minimize the localization error 13/23 Evaluation Track Design Experimental Setup Robot Design 14/23 Evaluation Back Empirical Power-Distance Relationship Insight: Only empirical power-distance relationship can provide high localization performance 120.00 Theoretical (N = 6) Power (dBm) 100.00 80.00 60.00 Theoretical (N = 3) 40.00 Empirical 20.00 Theoretical (N = 2) 0.00 Distance (Meters) 15/23 Evaluation 4 Euclidean Distance (Meters) 3.5 Localization Accuracy Insight: Performance can be improved by denser reference tag deployment Actual Position 3 2.5 2 Inferred Position 1.5 1 0.5 0 Location Measurement # 16/23 Evaluation Localization Time Insight: Faster algorithms provide lower tag detectability 25.00 Average Time (Seconds) Linear Search (LH) 20.00 15.00 Parallel Search 10.00 5.00 Binary Search Linear Search (HL) 0.00 Distance from Antenna (Meters) 17/23 Evaluation Localization Performance Vs #Tags Average Localization Error (Meters) Insight: Localization performance varies with tag density 1.6 1.4 1.2 1 0.8 0.6 0.4 Diminishing returns 0.2 0 Number of Reference Tags 18/23 Evaluation Comparative Evaluation Average Time (minutes) Approach Setup Phase Localization Phase Ni et al., 2003 - - Alippi et al., 2006 - - Bekkali et al., 2007 - - Senta et al., 2007 - - Wang et al., 2007 - Zhang et al., 2007 Test Area (m2) - Localization Error (m) 2 20 0.68 9 0.5 – 1.0 Pure RFID 2 0.2 - - 0.1 – 0.9 - - - Seo and Lee, 2008 - - Choi and Lee, 2009 - - Choi et al., 2009 - - - Joho et al., 2009 27 - - 161.23 29.78 47.24 1.67 0 161.23 5.28 1.42 1.95 1.67 0 10.32 Linear Search (LH) Linear Search (HL) Binary Search Parallel Search Measure and Report Combined Approach Notes 1 Hybrid 5 0.2 – 1.6 Pure RFID 14.4 0.02 Hybrid 8 0.21 0.38 0.27 0.29 0.31 0.35 0.25 0.18 Pure RFID Pure RFID 19/23 Applications Tier-I Applications Locating Objects Warehouses Hospitals Supply Chains Tier-II Applications Assisted Living Location-Aware Services Energy Saving in Buildings Monitor life-critical events Smart Carts Provide ground truth 20/23 Interface Object Location Visualization 21/23 Conclusion Future Directions RFID-only Object Localization Framework: - Showed that pure RFID can be used for object localization - Introduced a power-distance relationship metric - Proposed tag binning to mitigate tag sensitivity variability - Devised effective localization algorithms and heuristics - Identified / mitigated key localization challenges Future Research Directions: - Scalability - Technology Evolution - Localization performance - Visualization tools - Field testing and Commercialization 22/23 Milestones Research Deliverables Journal Publication: • Kirti Chawla, and Gabriel Robins, An RFID-Based Object Localization Framework, International Journal of Radio Frequency Identification Technology and Applications, Inderscience Publishers, 2011, Vol. 3, Nos. 1/2, pp. 2-30. Conference Publications: • • Kirti Chawla, Gabriel Robins, and Liuyi Zhang, Efficient RFID-Based Mobile Object Localization, Proceedings of IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, 2010, Canada, pp. 683-690. Kirti Chawla, Gabriel Robins, and Liuyi Zhang, Object Localization using RFID, Proceedings of IEEE International Symposium on Wireless Pervasive Computing, 2010, Italy, pp. 301-306. Patent: • Kirti Chawla, and Gabriel Robins, Object Localization with RFID Infrastructure, US Patent Application Number: PCT/US2011/053067, filed with WIPO/USPTO September 2011. Copyright: • Kirti Chawla, and Gabriel Robins, An RFID-Based Object Localization Framework, US Copyright Case Number: 1-633487801, 2011. Startup Venture: • • • Co-founded Diorama Technologies LLC, in partnership with private investors Raised venture capital funding and negotiated licensing terms Other investors have shown strong interest in commercializing our ideas 23/23 Patent WIPO/USPTO Object Localization with RFID Infrastructure Backup Slides Background Organizing Localization Space Localization Solutions Localization Type Environmental Localization Technique Signal Strength Signal Phase Self Arrival Time Approach Localization Challenges Back Radio Interference Occlusions Tag Sensitivity Tag Spatiality Tag Orientation Reader Locality Evaluation Tag Sensitivity – Single Tag Back Constant Distance/Variable Power 140 120 100 80 60 40 20 0 Cumulative Read Count 140 120 100 80 60 40 20 0 Cumulative Read Count 31.6 dBm Number of Tags 28.6 dBm Number of Tags Number of Tags 2.54 Meters, 25.6 dBm 140 120 100 80 60 40 20 0 Cumulative Read Count Variable Distance/Constant Power Cumulative Read Count 140 120 100 80 60 40 20 0 Cumulative Read Count 3.81 Meters Number of Tags 140 120 100 80 60 40 20 0 2.54 Meters Number of Tags Number of Tags 1.27 Meters, 31.6 dBm 140 120 100 80 60 40 20 0 Cumulative Read Count Evaluation Tag Sensitivity – Multi-Tag (Proximity) Back 2.54 Meters, 25.6 dBm 12 10 8 6 4 2 0 Multi-Tag Position 28.6 dBm Average Read Count 12 10 8 6 4 2 0 Average Read Count Average Read Count Constant Distance/Variable Power 12 10 8 6 4 2 0 Multi-Tag Position 31.6 dBm Multi-Tag Position 1.27 Meters, 31.6 dBm Multi-Tag Position 12 10 8 6 4 2 0 2.54 Meters Multi-Tag Position Average Read Count 12 10 8 6 4 2 0 Average Read Count Average Read Count Variable Distance/Constant Power 12 10 8 6 4 2 0 3.81 Meters Multi-Tag Position Tag Sensitivity – Multi-Tag (Rotation-1) Evaluation 16 14 12 10 8 6 4 2 0 31.6 dBm Multi-Tag Position Multi-Tag Position Average Read Count Average Read Count Multi-Tag Position 16 14 12 10 8 6 4 2 0 Multi-Tag Position Average Read Count 16 14 12 10 8 6 4 2 0 Multi-Tag Position Average Read Count 16 14 12 10 8 6 4 2 0 16 14 12 10 8 6 4 2 0 Multi-Tag Position 16 14 12 10 8 6 4 2 0 Multi-Tag Position 16 14 12 10 8 6 4 2 0 Multi-Tag Position Average Read Count Average Read Count Average Read Count 28.6 dBm 16 14 12 10 8 6 4 2 0 Multi-Tag Position Multi-Tag Position 16 14 12 10 8 6 4 2 0 Average Read Count 16 14 12 10 8 6 4 2 0 Average Read Count 2.54 Meters, 25.6 dBm Average Read Count 16 14 12 10 8 6 4 2 0 Constant Distance/Variable Power Average Read Count Average Read Count Back Multi-Tag Position 16 14 12 10 8 6 4 2 0 Multi-Tag Position Tag Sensitivity – Multi-Tag (Rotation-2) Evaluation 12 10 8 6 4 2 0 12 10 8 6 4 2 0 3.81 Meters Average Read Count Average Read Count Multi-Tag Position Multi-Tag Position Multi-Tag Position 12 10 8 6 4 2 0 Multi-Tag Position Average Read Count 12 10 8 6 4 2 0 Multi-Tag Position Average Read Count 2.54 Meters 12 10 8 6 4 2 0 Multi-Tag Position 12 10 8 6 4 2 0 Multi-Tag Position 12 10 8 6 4 2 0 Multi-Tag Position Average Read Count 12 10 8 6 4 2 0 12 10 8 6 4 2 0 Multi-Tag Position Average Read Count Average Read Count Multi-Tag Position Average Read Count 12 10 8 6 4 2 0 Average Read Count 1.27 Meters, 31.6 dBm Average Read Count 12 10 8 6 4 2 0 Variable Distance/Constant Power Average Read Count Average Read Count Back Multi-Tag Position 12 10 8 6 4 2 0 Multi-Tag Position Approach Error-Reducing Heuristics Back Absolute Difference Localization Error Minimum Power Selection Meta Heuristic Root Sum Square Problem: There can be multiple nearby reference tags Insight: Select nearby reference tags using different schemes