TY - JOUR
T1 - Integration of an IoT sensor with angle-of-arrival-based angle measurement in AGV navigation
T2 - A reliability study
AU - Cai, Zhen
AU - Zhang, Fanhang
AU - Tan, Yuan
AU - Kessler, Stephan
AU - Fottner, Johannes
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/11
Y1 - 2024/11
N2 - Automated guided vehicle (AGV), which was initially designed for indoor operations in industry, has been increasingly applied in outdoor heavy-duty logistics tasks. In typical navigation tasks, such as the autonomous tracking of a designated object or a person, relative angle and relative distance between AGV and the target is required. To obtain the necessary information, various on-board sensors are extensively integrated. In this paper, the reliability of measuring the relative angle with the Angle-of-Arrival (AoA) method with two different Internet of Things (IoT) sensor sets from Texas Instrument (TI) and u-blox, according to Bluetooth 5.1 was investigated. The performance of IoT sensors was validated with angle accuracy parameters and received signal strength indicator (RSSI). The better IoT sensor was then integrated into the AGV navigation system, and the information gathered from IoT sensor enabled the AGV to turn toward the direction of the target. The process of AGV turning to the targeted direction based on IoT sensor information was respectively tested in the simulation and actual environment and evaluated by the disparity between the real relative angle and the rotation angle of the AGV. The results showed that this disparity was within ±5° in both simulated and actual environments, and methods for higher accuracy were proposed. In this way, the reliability and performance of Angle of Arrival (AoA) sensors in measuring the relative angle, which remains unexplored by other researchers, was systematically assessed contributing to extending the usability of AoA sensors in complex, real-world applications.
AB - Automated guided vehicle (AGV), which was initially designed for indoor operations in industry, has been increasingly applied in outdoor heavy-duty logistics tasks. In typical navigation tasks, such as the autonomous tracking of a designated object or a person, relative angle and relative distance between AGV and the target is required. To obtain the necessary information, various on-board sensors are extensively integrated. In this paper, the reliability of measuring the relative angle with the Angle-of-Arrival (AoA) method with two different Internet of Things (IoT) sensor sets from Texas Instrument (TI) and u-blox, according to Bluetooth 5.1 was investigated. The performance of IoT sensors was validated with angle accuracy parameters and received signal strength indicator (RSSI). The better IoT sensor was then integrated into the AGV navigation system, and the information gathered from IoT sensor enabled the AGV to turn toward the direction of the target. The process of AGV turning to the targeted direction based on IoT sensor information was respectively tested in the simulation and actual environment and evaluated by the disparity between the real relative angle and the rotation angle of the AGV. The results showed that this disparity was within ±5° in both simulated and actual environments, and methods for higher accuracy were proposed. In this way, the reliability and performance of Angle of Arrival (AoA) sensors in measuring the relative angle, which remains unexplored by other researchers, was systematically assessed contributing to extending the usability of AoA sensors in complex, real-world applications.
KW - Angle-of-arrival
KW - Automated guided vehicle
KW - Bluetooth
KW - Internet of things
KW - Relative angle accuracy
UR - http://www.scopus.com/inward/record.url?scp=85207911869&partnerID=8YFLogxK
U2 - 10.1016/j.jii.2024.100707
DO - 10.1016/j.jii.2024.100707
M3 - Article
AN - SCOPUS:85207911869
SN - 2452-414X
VL - 42
JO - Journal of Industrial Information Integration
JF - Journal of Industrial Information Integration
M1 - 100707
ER -