Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals
<p>Schematic of the UHF RFID-based indoor autonomous localization and tracking system. The UHF RFID reader is placed on the vehicle, and tags are placed on the floor.</p> "> Figure 2
<p>The vehicle state transition of two adjacent points on the trajectory.</p> "> Figure 3
<p>Multipath propagation scenario of the indoor autonomous vehicle navigation system.</p> "> Figure 4
<p>Phase diagram for narrowband signaling propagation on a multipath channel.</p> "> Figure 5
<p>The localization and tracking results when RFID reader could read four neighboring tag. (<b>a</b>) The localization and tracking results of the line trajectory. (<b>b</b>) The localization and tracking results of the circular trajectory.</p> "> Figure 6
<p>The CDF curves of the circle trajectory tracking error with different numbers of tags.</p> "> Figure 7
<p>The CDF curves of the circle trajectory tracking and localization error with the RSS and phase.</p> ">
Abstract
:1. Introduction
- (1)
- A novel indoor mobile robot localization and navigation system was proposed. The RFID reader is mounted on the mobile robot and obtains the position of the robot by dual-frequency PDOA ranging. This system needs a much lower tag deployment density, which can reduce the tag reading collision.
- (2)
- To mitigate the multipath-caused ranging error, the localization problem was modeled as an optimization problem and relaxed to an SDP problem, which can be solved efficiently.
- (3)
- In order to improve system accuracy, the odometry information, obtained from wheel encoders, is fused with the RFID localization result. The system is transformed into a linear model, and a novel KF is presented to solve the tracking problem. Different from the nonlinear KF methods, the computational requirements are lower. Hence, the time efficiency of the proposed method is high.
2. Related Works
3. Problem Formulation
3.1. Autonomous Vehicle Movement Model
3.2. Autonomous Vehicle Localization Problem
3.3. UHF RFID Channel Model
4. Localization and Tracking Algorithm
Algorithm 1 UHF RFID-based indoor autonomous vehicle localization and tracking algorithm. |
Input: {}: Tags’ coordinates {}: PDOA ranging results : Original state vector : Original covariance matrix {}: The covariance of the process noise {}: The covariance of the observation noise Output: the autonomous vehicle position
|
5. Numerical Results
5.1. Simulation Configuration
5.2. Performance of Tracking with Different Trajectories
5.3. Performance of Tracking with Different Numbers of Tags
5.4. Comparison With an RSSI Ranging Method
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Experiment Setup | Mean Error (m) | RMSE (m) | ||
---|---|---|---|---|
Straight Line | Circle | Straight Line | Circle | |
Localization with four tags | 0.201 | 0.196 | 0.221 | 0.229 |
Tracking with four tags | 0.116 | 0.053 | 0.107 | 0.056 |
Localization with six tags | 0.158 | 0.163 | 0.172 | 0.181 |
Tracking with six tags | 0.075 | 0.032 | 0.072 | 0.028 |
Localization with eight tags | 0.142 | 0.137 | 0.167 | 0.152 |
Tracking with eight tags | 0.06 | 0.018 | 0.069 | 0.023 |
Localization with ten tags | 0.148 | 0.144 | 0.175 | 0.170 |
Tracking with ten tags | 0.087 | 0.02 | 0.093 | 0.032 |
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Zhang, Y.; Gong, X.; Liu, K.; Zhang, S. Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals. Sensors 2021, 21, 3286. https://doi.org/10.3390/s21093286
Zhang Y, Gong X, Liu K, Zhang S. Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals. Sensors. 2021; 21(9):3286. https://doi.org/10.3390/s21093286
Chicago/Turabian StyleZhang, Yunlei, Xiaolin Gong, Kaihua Liu, and Shuai Zhang. 2021. "Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals" Sensors 21, no. 9: 3286. https://doi.org/10.3390/s21093286
APA StyleZhang, Y., Gong, X., Liu, K., & Zhang, S. (2021). Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals. Sensors, 21(9), 3286. https://doi.org/10.3390/s21093286