aspg-18-4138-1792028089
20261015013449
American Scientific Publishing Group
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American Scientific Publishing Group
Journal of Intelligent Systems and Internet of Things
JISIoT
2769-786X
2690-6791
2025
17
2
Low-Cost Multi-Sensor Localization for Indoor AGVs
Nopparut
Khaewnak
School of Mechanical Engineering, Institute of Engineering, Suranaree University of Technology), Nakhon Ratchasima, Thailand
Siripong
Pawako
School of Mechanical Engineering, Institute of Engineering, Suranaree University of Technology), Nakhon Ratchasima, Thailand
Akkharachai
Kosiyanurak
School of Mechanical Engineering, Institute of Engineering, Suranaree University of Technology), Nakhon Ratchasima, Thailand
Suradet
Tantrairatn
School of Mechanical Engineering, Institute of Engineering, Suranaree University of Technology), Nakhon Ratchasima, Thailand
Jiraphon
Srisertpol
School of Mechanical Engineering, Institute of Engineering, Suranaree University of Technology), Nakhon Ratchasima, Thailand
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Indoor transportation systems are a key area of development, where Automated Guided Vehicles (AGVs) help to increase efficiency and reduce labor costs. However, high-precision positioning technologies such as LiDAR and GNSS are expensive, making them unsuitable for widespread use. This research has developed a low-cost positioning system for indoor AGVs using multiple sensors, including CCTV, UWB, inertial measurement units (IMUs), and encoders. The experiment was carried out under both static and dynamic conditions. In static tests, Trilateration distance measurements show a lower positioning error than the triangular method, with a maximum error of 1.4464 m (x-axis) and 1.0464 m (y-axis) in dynamic tests. The integrated Encoder and IMU sensor data yielded the lowest error (RMSE = 0.0732 m at 0.4 m/s, 0.0678 at 0.27 m/s), Next is CCTV, while UWB has the highest error rate. The application of a Parallel Sensor Fusion architecture optimized using a Generalized Reduced Gradient (GRG) nonlinear algorithm, significantly reduced localization errors. The RMSE values decreased to 0.0623 m (0.4 m/s) and 0.0411 m (0.27 m/s). The results, in a controlled environment laboratory, indicate that combining multiple sensors will improve the positioning accuracy. Combining the encoder and IMU effectively reduces accumulated errors and increases system stability. While Adjust the weight of the sensor offline, this proposed system offers a cost-effective positioning solution for indoor AGVs, which contributes to the development of affordable and accurate AGV navigation systems.
2025
295
310
4138
https://creativecommons.org/licenses/by/4.0/
10.54216/JISIoT.170219
https://americaspg.com/journal/18/article/4138
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https://americaspg.com/storage/51759250202.pdf