Avaliação de Unidade de Medição Inercial Utilizando Técnicas de Reconstrução de Trajetória de Pedestres
Resumo
Diversos trabalhos propuseram métodos para reconstruir trajetória e estimar a posição de pedestres baseando-se em unidades de medição inercial. Montando os sensores no pé é possível utilizar um filtro de Kalman estendido e com a técnica ZUPT lidar com os erros oriundos das medições dos sensores. Este trabalho busca analisar a influência das configurações de uma unidade de medição inercial de baixo custo nos resultados finais desses sistemas. As configurações dos sensores, relacionadas ao fundo de escala e sensibilidade de medição, foram estudadas comparando estatisticamente os erros de diferentes métodos de reconstrução de trajetória. Os resultados apontam o fundo de escala do giroscópio como o parâmetro mais influente do sistema, já a combinação configuração e algoritmo com melhor desempenho apresentam uma média dos erros de posicionamento de 0.98% da distância total percorrida.
Palavras-chave:
pedestrian dead reckoning, inertial measurement unit, ZUPT, extended Kalman filter, Madgwick, sistema de navegação inercial
Referências
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Y. Wu, H. B. Zhu, Q. X. Du, S. M. Tang, ”A survey of the research status of pedestrian dead reckoning systems based on inertial sensors,” International Journal of Automation and Computing, v. 16, n. 1, p. 65- 83, 2019.
X. Hou, J. Bergmann, ”Pedestrian dead reckoning with wearable sensors: A systematic review,” IEEE Sensors Journal, v. 21, n. 1, p. 143-152, 2020.
X. C. Zhou, J. X. Chen, Y. Dong, X. R. Lu, J. W. Cui, B. Y. Zheng, ”Pedestrian navigation with foot-mounted inertial sensors in wearable body area networks,” In: Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific. IEEE, 2014. p. 1-7.
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A. R. Jiménez, F. Seco, J. C. Prieto, J. Guevara, ”Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU,” In: 2010 7th workshop on positioning, navigation and communication. IEEE, 2010. p. 135-143.
S. Rajagopal, “Personal dead reckoning system with shoe mounted inertial sensors,” In Master of Science Thesis, Stockholm, Sweeden, 2008, pp. 1-45.
L. Zhang, Y. Liu, J. Sun, ”A Hybrid Framework for Mitigating Heading Drift for a Wearable Pedestrian Navigation System through Adaptive Fusion of Inertial and Magnetic Measurements,” Applied Sciences, v. 11, n. 4, p. 1902, 2021.
H. Li, H. Guo, Y. Qi, L. Deng, M. Yu, ”Research on multi-sensor pedestrian dead reckoning method with UKF algorithm,” Measurement, v. 169, p. 108524, 2021.
C. Fischer, P. T. Sukumar, M. Hazas, ”Tutorial: Implementing a pedestrian tracker using inertial sensors,” IEEE pervasive computing, v. 12, n. 2, p. 17-27, 2012.
J. Nilsson, I. Skog, P. Händel, K. V. S. Hari, ”Foot-mounted INS for everybody-an open-source embedded implementation,” In: Proceedings of IEEE/ION PLANS 2012. 2012. p. 140-145.
S. Qiu, Z., Wang, H. Zhao, K., Qin, Z. Li, H. Hu, ”Inertial/magnetic sensors based pedestrian dead reckoning by means of multi-sensor fusion,” Information Fusion, v. 39, p. 108-119, 2018.
Xin L., Yang W., ”Evaluation of AHRS algorithms for foot-mounted inertial-based indoor navigation systems,” Open Geosciences, v. 11, n. 1, p. 48-63, 2019.
S. Madgwick, A. Harrison, R. Vaidyanathan, ”Estimation of IMU and MARG orientation using a gradient descent algorithm,” In: 2011 IEEE international conference on rehabilitation robotics. IEEE, 2011. p. 1-7.
R. Mahony, T. Hamel, JM. Pflimlin, ”Nonlinear complementary filters on the special orthogonal group,” IEEE Transactions on automatic control, v. 53, n. 5, p. 1203-1218, 2008.
M. L. Hoang, A. Pietrosanto, ”Yaw/Heading optimization by drift elimination on MEMS gyroscope,” Sensors and Actuators A: Physical, v. 325, p. 112691, 2021.
Y. Wu, H. B. Zhu, Q. X. Du, S. M. Tang, ”A survey of the research status of pedestrian dead reckoning systems based on inertial sensors,” International Journal of Automation and Computing, v. 16, n. 1, p. 65- 83, 2019.
X. Hou, J. Bergmann, ”Pedestrian dead reckoning with wearable sensors: A systematic review,” IEEE Sensors Journal, v. 21, n. 1, p. 143-152, 2020.
X. C. Zhou, J. X. Chen, Y. Dong, X. R. Lu, J. W. Cui, B. Y. Zheng, ”Pedestrian navigation with foot-mounted inertial sensors in wearable body area networks,” In: Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific. IEEE, 2014. p. 1-7.
M. V. Potter, L. V. Ojeda, N. C. Perkins, S. M. Cain, ”Effect of IMU design on IMU-derived stride metrics for running,” Sensors, v. 19, n. 11, p. 2601, 2019.
Publicado
22/11/2021
Como Citar
ROCHA E SILVA, Rodolfo Nícolas; GONÇALVES, Glauco Estácio; MEDEIROS, Victor Wanderley Costa de.
Avaliação de Unidade de Medição Inercial Utilizando Técnicas de Reconstrução de Trajetória de Pedestres. In: ARTIGOS COMPLETOS - SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SISTEMAS COMPUTACIONAIS (SBESC), 11. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 24-31.
ISSN 2763-9002.
DOI: https://doi.org/10.5753/sbesc_estendido.2021.18490.
