Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Indirect Kalman Filter based Sensor Fusion for Error Compensation of Low-Cost Inertial Sensors and Its Application to Attitude and Position Determination of Small Flying robot

저가 관성센서의 오차보상을 위한 간접형 칼만필터 기반 센서융합과 소형 비행로봇의 자세 및 위치결정

  • 박문수 (아주대학교 전자공학부) ;
  • 홍석교 (아주대학교 전자공학부)
  • Published : 2007.07.01
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Abstract

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

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References

  1. P. Li, W. TianMiao, L. JianHon, and W. Song, 'An attitude estimate approach using MEMS sensors for small UAVs,' IEEE International Conference on Industrial Informatics, pp. 1113-1117, Aug. 2006
  2. A. K. Broun, 'GPS/INS uses low-cost MEMS IMU,' IEEE Aerospace and Electronic Systems Magazine, vol. 20, no. 4, pp. 3-10, Sep. 2005
  3. N. Metni, J. M. Pflimlin, and T. Hamel, et al, 'Attitude and gyro bias estimation for a VTOL UAV,' Control Engineering Practice, vol. 14, no. 12, pp. 1511-1520, Dec. 2004
  4. D. H. Lyon, 'A military perspective on small unmanned aerial vehicles,' IEEE Instrumentation & Measurement Magazine, vol. 7, no. 3, pp. 27-31, Sep. 2004 https://doi.org/10.1109/MIM.2004.1304563
  5. S. K. Hong, 'Fuzzy logic based closed-loop strapdown attitude system for Unmanned Aerial Vehicle(UAV),' Sensors and Actuators A-Physical, vol. 107, no. 2, pp. 109-118, Oct. 2003 https://doi.org/10.1016/S0924-4247(03)00353-4
  6. D. Loebis, R. Sutton, and J. Chudley, et al., 'Adaptive tuning of a Kalman filter via fuzzy logic for an intelligent AUV navigation system,' Control Engineering Practice, vol. 12, no. 12, pp. 1531-1539, Dec. 2004 https://doi.org/10.1016/j.conengprac.2003.11.008
  7. A. Huster, E. W. Frew, and S. M. Rock, 'Relative position estimation for AUVs by fusing bearing and inertial rate sensor Measurements,' Proc. MTS/IEEE Oceans, pp. 1863-1870, Oct. 2002
  8. G. Grenon, P. E. An, S. M. Smith, and A. J. Healey, 'Enhancement of the inertial navigation system for the morpheus autonomous unerwater vehicle,' IEEE Journal of Oceanic Engineering, vol. 26, no. 4, pp. 548-560, Oct. 2001 https://doi.org/10.1109/48.972091
  9. X. Yun, E. R. Bachmann, and Suat Arslan, 'An Inertial navigation system for small autonomous underwater vehicles,' Proc. IEEE International Conference of Robotics & Automation, pp. 1781-1786, Oct. 2001
  10. X. Yun, E. R. Bachmann, and S. Arslan, 'An inertial navigation system for small autonomous underwater vehicles,' Proc. IEEE Int. Conf. on Robotics and Automation, pp. 1781-1786, 2000. 4
  11. G. Ippoliti, L. Jetto, and S. Longhi, 'Localization of mobile robots: Development and comparative evaluation of algorithms based on odometric and inertial sensors,' Journal of Robotic Systems, vol. 22, no. 12, pp. 725-735, Dec. 2005 https://doi.org/10.1002/rob.20095
  12. S. Panzieri, F. Pascucci, and G. Ulivi, 'An outdoor navigation system using GPS and inertial platform,' IEEE Trans. on Mechatronics, vol. 7, no. 2, pp. 134-142, Jun. 2002 https://doi.org/10.1109/TMECH.2002.1011250
  13. S. I. Roumeliotis, G. S. Sukhatme, and G. A. Bekey, 'Smoother based 3D attitude estimation for mobile robot localization,' Proc. of IEEE Int. Conf. on Robotics and Automation, vol. 3, pp. 1979-1986, Oct. 1999
  14. B. Barshan and H. Durrant-Whyte, 'Inertial navigation systems for mobile robots,' IEEE Trans. on Robotics and Automation, vol. 11, no. 3, pp. 328-342, Jun. 1995 https://doi.org/10.1109/70.388775
  15. 정광윤, 조영석, 심덕선, '무인탐사체 항법을 위한 GPS/INS 초강결합 성능분석,' 제어.자동화.시스템공학 논문지, 제 12 권, 제 8 호, pp. 773-779, Aug. 2006 https://doi.org/10.5302/J.ICROS.2006.12.8.773
  16. S. Y. Cho and W. S. Choi, 'Robust positioning technique in lowcost DR/GPS for land navigation,' IEEE Trans. on Instrumentation and Measurement, vol. 55, no. 4, pp. 1132-1142, Aug. 2006 https://doi.org/10.1109/TIM.2006.877718
  17. L. B. Cremean, et. al., 'Alice: An information-rich autonomous vehicle for high-speed desert navigation,' Journal of Robotic Systems, vol. 23, no. 9, pp. 777-810, Sep. 2006
  18. D. M. Bevly, 'Global Positioning System(GPS): A low-cost velocity sensor for correcting inertial sensor errors on ground vehicle,' Journal of Dynamic Systems Measurement and Control Trans. of The ASME, vol. 126, no. 2, pp. 255-264, Jun. 2004 https://doi.org/10.1115/1.1766027
  19. J. P. Wang, W. F. Tian, and Z. H. Jin, 'Study on integrated micro inertial navigation systems/GPS for land vehicles,' Proc. intelligent transportation systems, vol. 2, pp. 1650-1553, Oct. 2003
  20. H. Janocha and B. Diewald, 'ICAROS: Over-all-calibration of industrial robots,' Industrial Robot: An International Journal, vol. 22, no. 3, pp. 15-20, Jun. 1995
  21. J Gao, P. Webb, and N. Gindy., 'Research on an inertial positioning system for a parallel Kinematic machine,' mechatronics, vol. 15, no. 1, pp. 1-22, Feb. 2005 https://doi.org/10.1016/j.mechatronics.2004.07.001
  22. J. Gao, P. Webb, and N. Gindy., 'Error reduction for an inertialsensor-based dynamic parallel Kinematic machine positioning system,' Measurement Science & Technology, vol. 14, no. 5, pp. 543-550, May 2003 https://doi.org/10.1088/0957-0233/14/5/302
  23. G. Pang and Hl Liu, 'Evaluation of a low-cost MEMS accelerometer for distance measurement,' Journal of Intelligent and Robotic Systems, vol. 30, pp. 249-256, 2001 https://doi.org/10.1023/A:1008113324758
  24. W. Hao, and W. F. Tian, 'Modeling the random drift of micromachined gyroscope with neural network,' Neural Processing Letters, vol. 22, no. 3, pp. 235-247, Dec. 2005 https://doi.org/10.1007/s11063-005-6800-8
  25. S. Hong, M. H. Lee, and H. H. Chun, et al., 'Experimental study on the estimation of lever arm in GPS/INS,' IEEE Trans. on Vehicular Technology, vol. 55, no. 2, pp. 431-448, Mar. 2006 https://doi.org/10.1109/TVT.2005.863411
  26. Y. S. Suh, S. K. Park, and H. J. Kang, et al, 'Attitude estimation adaptively compensating external acceleration,' JSME Int. journal series C-mechanical systems machine elements and manufacturing, vol. 49, no. 1, pp. 172-179, Mar. 2006 https://doi.org/10.1299/jsmec.49.172
  27. 김광진, 박찬국, 유명종, 박영범, 'INS/GPS 강결합 기법에 대한 EKF와 UKF의 성능 비교,' 제어.자동화.시스템공학 논문지, 제 12 권, 제 8 호, pp. 780-788, 2006. 8 https://doi.org/10.5302/J.ICROS.2006.12.8.780
  28. S. P. Hong, M. H. Lee, and H. H. Chun, et al., 'Observability of error states in GPS/INS integrations,' IEEE Trans. on Vehicular Technology, vol. 54, no. 2, pp. 731-743, Mar. 2005 https://doi.org/10.1109/TVT.2004.841540
  29. S. Park, C. W. Tan, and J. Park, 'A scheme for improving the performance of a gyroscope-free inertial measurement unit,' Sensors and Actuators A-Physical, vol. 121, no. 2, pp. 410-420, Jun. 2005 https://doi.org/10.1016/j.sna.2005.03.060
  30. C. Hide and T. Moore, 'GPS and low cost INS integration for positioning in the Urban environment,' Proceedings of ION GNSS 2005, 2005. 9
  31. D. H. Hwang, S. H. Oh, and S. J. Lee, et al, 'Design of a lowcost attitude determination GPS/INS integrated navigation system,' GPS Solutions, vol. 9, no. 4, pp. 294-311, Nov. 2005 https://doi.org/10.1007/s10291-005-0135-9
  32. N. S. Kumar and T. Jann, 'Estimation of attitudes from a lowcost miniaturized inertial platform using Kalman filter-based sensor fusion algorithm,' Sadhana-Academic Proceedings in Engineering Sciences, vol. 29, pp. 217-235, Apr. 2004
  33. M. Haid and J. Breitenbach, 'Low cost inertial orientation tracking with Kalman filter,' Applied Mathematics and Computation, vol. 153, no. 2, pp. 567-575, Jun. 2004 https://doi.org/10.1016/S0096-3003(03)00656-8

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