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Orientation Of A Triaxial Accelerometer Using A Homogeneous Transformation Matrix And Kalman Filters

Open Access
|Dec 2014

References

  1. K.-S. Kim, T.-H. Yoon, J.-W. Lee, D.-J. Kim, Interactive toothbrushing education by a smart toothbrush system via 3D visualization., Comput. Methods Programs Biomed. 96 (2009) 125–132. doi:10.1016/j.cmpb.2009.04.006.10.1016/j.cmpb.2009.04.00619439390
  2. K. Morioka, F. Hashikawa, T. Takigawa, Human Identification Based on Walking Detection with Acceleration Sensor and Networked Laser Range Sensors in Intelligent Space, Int. J. Smart Sens. Intell. Syst. 6 (2013) 2040–2054.
  3. M.J. Mathie, B.G. Celler, N.H. Lovell, A.C.F. Coster, Classification of basic daily movements using a triaxial accelerometer, Med. Biol. Eng. Comput. (2004) 679–687.10.1007/BF0234755115503970
  4. B. Kikhia, M. Gomez, L.L. Jiménez, J. Hallberg, N. Karvonen, K. Synnes, Analyzing body movements within the Laban Effort Framework using a single accelerometer., Sensors. 14 (2014) 5725–41. doi:10.3390/s140305725.10.3390/s140305725400401724662408
  5. C.C. Yang, Y.L. Hsu, A review of accelerometry-based wearable motion detectors for physical activity monitoring., Sensors. 10 (2010) 7772–88. doi:10.3390/s100807772.10.3390/s100807772323118722163626
  6. T. Paul, J. Singh, M.M. Nayak, K. Rajanna, M.S. Kumar, Design and optimization of bulk micromachinaded accelerometer for space applications, Int. J. Smart Sens. Intell. Syst. 1 (2008) 1019–1030.
  7. M.D. Djurić-Jovičić, N.S. Jovičić, D.B. Popović, Kinematics of gait: new method for angle estimation based on accelerometers., Sensors. 11 (2011) 10571–85. doi:10.3390/s111110571.10.3390/s111110571327430122346659
  8. W. Hernández, Improving the Responses of Several Accelerometers Used in a Car Under Performance Tests by Using Kalman Filtering, Sensors. 1 (2001) 38–52.10.3390/s10100038
  9. W. Hernández, Improving the Response of a Rollover Sensor Placed in a Car under Performance Tests by Using a RLS Lattice Algorithm, Sensors. 5 (2005) 613–632. doi:10.3390/s5120613.10.3390/s5120613
  10. L. Gasbarro, A. Beghi, R. Frezza, F. Nori, C. Spagnol, Motorcycle trajectory reconstruction by integration of vision and MEMS accelerometers, in: 43rd IEEE Conf. Decis. Control, IEEE, Atlantis, Paradise Island, 2004: pp. 779–783. doi:10.1109/CDC.2004.1428759.10.1109/CDC.2004.1428759
  11. D. Giansanti, G. Maccioni, V. Macellari, The development and test of a device for the reconstruction of 3-D position and orientation by means of a kinematic sensor assembly with rate gyroscopes and accelerometers., IEEE Trans. Biomed. Eng. 52 (2005) 1271–7. doi:10.1109/TBME.2005.847404.10.1109/TBME.2005.84740416041990
  12. H.H.S. Liu, G.K.H. Pang, Accelerometer for mobile robot positioning, IEEE Trans. Ind. Appl. 37 (2001) 812–819. doi:10.1109/28.924763.10.1109/28.924763
  13. J. Hwang, H. Yun, S.-K. Park, D. Lee, S. Hong, Optimal methods of RTK-GPS/accelerometer integration to monitor the displacement of structures., Sensors. 12 (2012) 1014–34. doi:10.3390/s120101014.10.3390/s120101014327925222368508
  14. R. Raya, E. Rocon, J. a Gallego, R. Ceres, J.L. Pons, A robust kalman algorithm to facilitate human-computer interaction for people with cerebral palsy, using a new interface based on inertial sensors., Sensors. 12 (2012) 3049–3066. doi:10.3390/s120303049.10.3390/s120303049337656522736992
  15. W.T. Ang, S.Y. Khoo, P.K. Khosla, C.N. Riviere, Physical model of a MEMS accelerometer for low-g motion tracking applications, in: IEEE Int. Conf. Robot. Autom. 2004. Proceedings. ICRA ‘04. 2004, IEEE, New Orleans. LA, 2004: pp. 1345–1351. doi:10.1109/ROBOT.2004.1308011.10.1109/ROBOT.2004.1308011
  16. M. Meng, Z. Wu, Y. Yu, Y. Ge, Y. Ge, Design and Characterization of a Six-axis Accelerometer*, in: Proc. 2005 IEEE Int. Conf. Robot. Autom., IEEE, Barcelona, Spain, 2005: pp. 2356–2361.
  17. J. Yang, W. Chang, W.C. Bang, E.S. Choi, Analysis and compensation of errors in the input device based on inertial sensors, Proc. Int. Conf. Inf. Technol. Coding Comput. 2 (2004) 790–796. doi:10.1109/ITCC.2004.1286755.10.1109/ITCC.2004.1286755
  18. M. ŠIPOŠ, J. ROHÁÄŒ, P. NOVÁÄŒEK, Analyses of Electronic Inclinometer Data for Tri-axial Accelerometer’s Initial Alignment, Pe.org.pl. (2012) 286–290.
  19. M. Sotak, Testing the Coarse Alignment Algorithm Using Rotation Platform, Acta Polytech. Hungarica. 7 (2010).
  20. R.E. Kalman, R.S. Bucy, New Results in Linear Filtering and Prediction Theory, Trans. ASME–Journal Basic Eng. 83 (1961) 95–108. doi:10.1115/1.3658902.10.1115/1.3658902
  21. R.E. Kalman, A new approach to linear filtering and prediction problems, Trans. ASME– Journal Basic Eng. 82 (1960) 35–45.10.1115/1.3662552
  22. G. Pappas, M. Zohdy, Extended Kalman Filtering and Pathloss modeling for Shadow Power Parameter Estimation in Mobile Wireless Communications, Int. J. Smart Sens. Intell. Syst. 7 (2014) 898–924.
Language: English
Page range: 1631 - 1646
Submitted on: Aug 20, 2014
Accepted on: Nov 6, 2014
Published on: Dec 1, 2014
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2014 J.-S. Botero V., W. Hernández, E. Fernández, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.