High-Accuracy Localization in Large-Scale Warehouse
Overview
This project aims to provide high accuracy localization services in large-scale warehouse, which can be divided into RFID and Bluetooth Parts. In the first phase, we did elaborative theoretical studies on RFID localization technology and reached centimeter level localization of tagged objects via RF-Robot. We realized both absolute localization (derive the fixed position of object RFID tag) as well as corporative relative localization (locate the relative position of two relative moving RFID tags) in static and moving scenarios. In addition to RFID localization, we also study Bluetooth localization based on Bluetooth 5.0 technology since compared to RFID, Bluetooth has the advantage of much longer transmission distance, capable of bidirectional communication and much stronger resistance against to noise, etc. We developed a IoT platform that can perform real-time localization of moving personnel and goods in large scale warehouse based on Bluetooth technology. We have so far delivered a series of publications, including several journal papers and conference papers, and developed the localization systems. Moreover, we demonstrated our localization system to Alibaba Cainiao at Alibaba Tianmao's logistics warehouse in Hangzhou, China.
Demo
Achievements
- Xiulong Liu, Jiannong Cao, Yanni Yang, Keqiu Li, Didi Yao, "Fast RFID Sensory Data Collection: Trade-off Between Computation and Communication Costs", IEEE Transactions on Networking (TON). 27(3): 1179-1191
- Xiulong Liu, Jiuwu Zhang, Shan Jiang, Yanni Yang, Keqiu Li, Jiannong Cao, Jiangchuan Liu, "Accurate Localization of Tagged Objects Using Mobile RFID-augmented Robots", IEEE Transactions on Mobile Computing (TMC), 20(4): 1273-1284
- Xiulong Liu, Jiannong Cao, Keqiu Li, Jia Liu, Xin Xie, "Efficient Range Queries for Large-scale Sensor-augmented RFID Systems", in IEEE Transactions on Networking (TON), 27(5): 1873 – 1886
- Zhuo Li, Jiannong Cao, Xiulong Liu, Jiuwu Zhang, Haoyuan Hu, Didi Yao, "A Self-Adaptive Bluetooth Indoor Localization System using LSTM-based Distance Estimator", The 29th International Conference on Computer Communications and Networks (ICCCN 2020), 3-5 August 2020. Virtual Conference
Members
Shan Jiang, Yanni Yang
Previous members include Xiulong Liu, Zhuo Li, Jiaqi Shuang, Jiuwu Zhang. Thanks for their contributions.