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The measurement of displacement with the use of MEMS sensors : accelerometer, gyroscope and magnetometer

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EN
Abstrakty
EN
The paper presents the method of determining the global orientation of links of the measuring arm by gauging the angles of the links relative to the vector of the gravitational and magnetic field using inertial sensors. A method of using Kalman filter to average the results is presented as a test on two-links measuring arm equipped with accelerometers and magnetometers placed on each of the links and analysis of measurement results in terms of repeatability. There was demonstrated the ability of creating kinematic chain. Instead of determining the position of the final link on the basis of the measurement of angles in relation to the previous links from the end to the base of the arm, it is possible to define links global orientation by measuring angles of links in reference to the vectors of the gravity field and the magnetic field, in global coordinate system.
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autor
  • Lodz University of Technology, Institute of Machine Tools and Production Engineering, 1/15 B. Stefanowskiego Street, 90-924 Lodz, Poland
  • Lodz University of Technology, Institute of Machine Tools and Production Engineering, 1/15 B. Stefanowskiego Street, 90-924 Lodz
autor
  • Lodz University of Technology, Institute of Electronics , 211/215 Wolczanska Street, 90-924 Lodz
autor
  • Lodz University of Technology, Institute of Machine Tools and Production Engineering, 1/15 B. Stefanowskiego Street, 90-924 Lodz
Bibliografia
  • [1] P. Cheng, B. Oelmann, “Joint-Angle Measurement Using Accelerometers and Gyroscopes—A Survey”, IEEE Transactions On Instrumentation And Measurement vol. 59, no. 2, 2010, 404–414. DOI: 10.1109/TIM.2009.2024367.
  • [2] M. El-Gohary, J. McNames, “Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm”, IEEE Transactions On Biomedical Engineering, vol. 62, no. 7, 2015, 1759–1767. DOI: 10.1109/TBME.2015.2403368.
  • [3] M. Quigley et al., “Low-cost Accelerometers for Robotic Manipulator Perception”. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 18–22, 2010, 6168–6174.DOI: 10.1109/IROS.2010.5649804.
  • [4] Y. Wang, B. Pitzer, “Manipulator State Estimation with Low Cost Accelerometers and Gyroscopes”. In: ed. Philip Roan, Nikhil Deshpande, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 7–12, 2012, 4822–4827.DOI: 10.1109/IROS.2012.6385893.
  • [5] M. Xu, N. Fan, Z. Wang, “Study on Extended Kalman Filtering for Attitude Estimation of Micro Flight Vehicle”. In: Third International Conference on Measuring Technology and Mechatronics Automation, vol. 3, 2011, 457–460. DOI: 10.1109/ICMTMA.2011.685.
  • [6] H. Zhao , Z. Wang, “Motion Measurement Using Inertial Sensors, Ultrasonic Sensors, and Magnetometers With Extended Kalman Filter for Data Fusion”, IEEE Sensors Journal, vol. 12, no. 5, 2012, 943–953. DOI: 10.1109/JSEN.2011.2166066.
  • [7] Ł. Frącczak, L. Podsędkowski, A. Kobierska, “Data fusion using Fuzzy Logic techniques supported by Modified Weighting factors (FLMW)”, International Journal of Fuzzy Systems, vol. 18, no. 1, 2016, 72-80. DOI: 10.1007/s40815-015-0095-3.
  • [8] L. Podsędkowski, H. Podsędkowska „The adaptive optimal Finite Impulse Response smoothing for off - line estimation of the states of the system described by discrete state space model using Extended Output Vector”, Methods and Models in Automation and Robotics MMAR 2015, 1179–1184. DOI: 10.1109/MMAR.2015.7283984.
  • [9] P. Żak, “Using 9-axis Sensor for Precise Cardiosurgical Robot Master Angular Position Determination”, Solid State Phenomena, vol. 199, 2013, 356–361.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-587182a9-5d31-40e2-8edb-e63f7e221c89
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