Evaluation of Battery-free UHF-RFID Sensor Wireless Signals for In-pipe Robotic Applications

Abstract

A reliable robotic localization method is required for comparing three-dimensional pipe maps obtained via laser scans at various times for accurately monitoring the evolution of internal pipe surface defects. Existing robotic localization methods have limitations when visual features vanish due to changes in the pipe environment or when encoder data becomes highly uncertain due to long-distance robotic traverses. To address this issue, we leverage battery-free ultra-high frequency radio frequency identification (UHF-RFID) sensors for transmitting wireless signals to a two-antenna reader integrated mobile robotic system. Although there are literature on the investigation of UHFRFID behaviors and their applications in indoor environments, analysis of the same for in-pipe scenarios was not well studied. In this paper, we evaluate the UHF-RFID sensor signals inside a field extracted pipeline. Firstly, we examine the UHF-RFID sensor signal patterns through repeated robotic scans. Secondly, we examine how the placement of UHF-RFID reader antennas affects the transmission of UHF-RFID sensor signals, as well as we study the effects of robotic traverse direction and speed on the UHF-RFID wireless signals. Finally, we examine whether identical UHF-RFID sensors generate the same pattern when placed in a pipeline. Overall, the experimental evaluation demonstrates that the use of two-antenna UHF-RFID readers can ameliorate the capabilities of robotic localization in the pipeline.

Battery-Free UHF-RFID Sensors-Based SLAM for In-Pipe Robot Perception

“…Data for training the measurement model was collected by placing UHF-RFID tags in the middle of the side wall of 5 meters long, 600-millimeter diameter pipe section. According to our previous studies [32] all tags perform similarly, and RFID tags did not interfere with each other. The closer the RFIDs were packed, the more the measurements were received.…”

“…Performance of the proposed algorithm was compared with industry standard, commonly used encoder odometry based robot localization (OD) and also with the Gaussian process combined particle filter based two antenna model localization method (GPPF2) we have proposed in our preliminary research work [31], [32].…”

“…Unlike RFID localization in outdoor or indoor applications, the highest peak of signal intensity is not always referring to the most likely location of the RFID tag [29], [30]. The pipe surface behaves like a waveguide causing the signal inside to bounce leading to various peaks and ripple effects in the signal strength [31], [32]. Furthermore, commercial off-the-shelf (COTS) RFID readers offer erratic measurements, only capable of accurately localizing the RFID tag within a square meter area [33], making the process difficult and unique.…”

“…The Gaussian process combined particle filter localization methodology using UHF-RFID signals has been proposed in our previous research [31], [32], [34], and it takes advantage of both Received Signal Strength Indicator (RSSI) and Phase data values to improve accuracy. It works well with known RFID distribution maps (RFID tag locations are known), and it has millimetre-level accuracy when using known RFID distribution maps.…”