TY  - CONF
AU  - Petrović, Milica
AU  - Wolniakowski, Adam
AU  - Ciezkowski, M.
AU  - Romaniuk, Slawomir
AU  - Miljković, Zoran
PY  - 2020
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3441
AB  - Mobile robot positioning is a crucial problem in modern industrial autonomous solutions. Lateration Positioning Systems base on the distance measurements to estimate the object's position. These measurements are however often affected by numerous sources of noise: obstacles, multi-pathing, signal propagation speed etc. Effective calibration methods are therefore required to eliminate these errors to achieve precise positioning. In this paper, we present the application of neural networks to improve the accuracy of a UWB lateration system. We present the network architecture and demonstrate how it can be used to alleviate the effects of multi-pathing and environment anisotropy in a real positioning setup. We furthermore compare the efficiency of the neural network with the state-of-the-art calibration methods.
PB  - Institute of Electrical and Electronics Engineers Inc.
C3  - 15th International Conference Mechatronic Systems and Materials, MSM 2020
T1  - Neural network-based calibration for accuracy improvement in lateration positioning system
DO  - 10.1109/MSM49833.2020.9201646
ER  - 

@conference{
author = "Petrović, Milica and Wolniakowski, Adam and Ciezkowski, M. and Romaniuk, Slawomir and Miljković, Zoran",
year = "2020",
abstract = "Mobile robot positioning is a crucial problem in modern industrial autonomous solutions. Lateration Positioning Systems base on the distance measurements to estimate the object's position. These measurements are however often affected by numerous sources of noise: obstacles, multi-pathing, signal propagation speed etc. Effective calibration methods are therefore required to eliminate these errors to achieve precise positioning. In this paper, we present the application of neural networks to improve the accuracy of a UWB lateration system. We present the network architecture and demonstrate how it can be used to alleviate the effects of multi-pathing and environment anisotropy in a real positioning setup. We furthermore compare the efficiency of the neural network with the state-of-the-art calibration methods.",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
journal = "15th International Conference Mechatronic Systems and Materials, MSM 2020",
title = "Neural network-based calibration for accuracy improvement in lateration positioning system",
doi = "10.1109/MSM49833.2020.9201646"
}

Petrović, M., Wolniakowski, A., Ciezkowski, M., Romaniuk, S.,& Miljković, Z.. (2020). Neural network-based calibration for accuracy improvement in lateration positioning system. in 15th International Conference Mechatronic Systems and Materials, MSM 2020
Institute of Electrical and Electronics Engineers Inc...
https://doi.org/10.1109/MSM49833.2020.9201646

Petrović M, Wolniakowski A, Ciezkowski M, Romaniuk S, Miljković Z. Neural network-based calibration for accuracy improvement in lateration positioning system. in 15th International Conference Mechatronic Systems and Materials, MSM 2020. 2020;.
doi:10.1109/MSM49833.2020.9201646 .

Petrović, Milica, Wolniakowski, Adam, Ciezkowski, M., Romaniuk, Slawomir, Miljković, Zoran, "Neural network-based calibration for accuracy improvement in lateration positioning system" in 15th International Conference Mechatronic Systems and Materials, MSM 2020 (2020),
https://doi.org/10.1109/MSM49833.2020.9201646 . .