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Using the Kalman filter in the quadrotor vehicle trajectory tracking system

  • Automation Systems in Scientific Research and Industry
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Optoelectronics, Instrumentation and Data Processing Aims and scope

Abstract

A problem of control of quadrotor vehicle motion over a trajectory defined implicitly in the coordinate space is considered. The previously proposed system of automated control of quadrotor vehicle flight is supplemented with relations based on an extended Kalman filter for estimating the plant state vector and the systematic error of measurements. The workability of the control system in the presence of the measurement noise is verified by results of modeling and experiments with the AR.Drone quadrotor vehicle.

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References

  1. D. J. Pines and F. Bohorquez, “Challenges Facing Future Micro-Air-Vehicle Development,” J. Aircraft 43(2), 290–305 (2006).

    Article  Google Scholar 

  2. S. Bouabdallah, P. Murrieri, and R. Siegwart, “Design and Control of an Indoor Micro Quadrotor,” in Proc. of the IEEE Intern. Conf. on Robotics and Automation (ICRA), New Orleans, USA (IEEE, 2004), pp. 4393–4398.

    Google Scholar 

  3. P.-J. Bristeau, F. Callou, D. Vissiere, and N. Petit, “The Navigation and Control Technology Inside the AR.Drone Micro UAV,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 1477–1484.

  4. M. Cutler, N. Kemal Ure, B. Michini, and J. P. How, “Comparison of Fixed and Variable Pitch Actuators for Agile Quadrotors,” in Proc. of the AIAA Guidance, Navigation, and Control Conference (GNC), Portland, USA, 2011, AIAA-2011-6406.

  5. G. M. Hoffmann, H. Huang, S. L. Wasland, and E.-C. J. Tomlin, “Quadrotor Helicopter Flight Dynamics and Control: Theory and Experiment,” in Proc. of the AIAA Guidance, Navigation, and Control Conference, Hilton Head, USA, 2007.

    Google Scholar 

  6. B. Lotfi and A. Azgal, “Trajectory Generation and Tracking of a Mini-Rotorcraft,” in Proc. of the IEEE Intern. Conf. on Robotics and Automation (ICRA), Barcelona, Spain (IEEE, 2005), pp. 2618–2623.

    Google Scholar 

  7. YU. S. Belinskaya and V. N. Chetverikov, “Control of a Quadrotor Helicopter,” Nauka Obraz., No. 5, 157–171 (2012).

    Google Scholar 

  8. S. Bouabdallah and R. Siegwart, “Backstepping and Sliding-Mode Techniques Applied to an Indoor Micro Quadrotor,” in Proc. of the IEEE Intern. Conf. on Robotics and Automation (ICRA), Barcelona, Spain (IEEE, 2005), pp. 2247–2252.

    Google Scholar 

  9. D. Mellinger and V. Kumar, “Minimum Snap Trajectory Generation and Control for Quadrotors,” in Proc. of the IEEE Intern. Conf. on Robotics and Automation (ICRA), Shanghai, China (IEEE, 2011), pp. 2520–2525.

    Google Scholar 

  10. J. Engel, J. Sturm, and D. Cremers, “Accurate Figure Flying with a Quadrocopter Using Onboard Visual and Inertial Sensing,” in Proc. of the Workshop on Visual Control of Mobile Robots (ViCoMoR) at the IEEE/RJS Intern. Conf. on Intelligent Robots and Systems (IROS), Vilamoura, Algarve, Portugal, Oct. 11, 2012, pp. 43–48.

  11. Yu. N. Zolotukhin and A. A. Nesterov, “Inverted Pendulum Control with Allowance for Energy Dissipation,” Avtometriya 46(5), 3–10 (2010) [Optoelectron., Instrum., Data Process. 46 (5), 401–407 (2010)].

    Google Scholar 

  12. S. A. Belokon’, YU. N. Zolotukhin, A. A. Nesterov, and M. N. Filippov, “Control of a Quadrotor Vehicle by Means of Organizing its Motion over a Desired Trajectory in the Space of States,” in Proc. XIII Intern. Conf. “Problems of Control and Modeling in Complex Systems,” (Samara Research Center, Samara, 2011), pp. 217–222.

    Google Scholar 

  13. S. A. Belokon, Yu. N. Zolotukhin, A. S. Mal’tsev, et al., “Control of Flight Parameters of a Quadrotor Vehicle Moving over a Given Trajectory,” Avtometriya 48(5), 32–41 (2012) [Optoelectron., Instrum. Data Process. 48 (5), 454–461 (2012)].

    Google Scholar 

  14. A. Martinelli and R. Siegwart, “Estimating the Odometry Error of a Mobile Robot during Navigation,” in European Conference on Mobile Robots (ECMR), Warsaw, Poland, Sept. 4–6, 2003, Vol. 1.

  15. W.-S. Choi, J.-G. Kang, and S.-Y. Oh, “Measurement Noise Estimator Assisted Extended Kalman Filter for Slam Problem,” in Proc. of the 2009 IEEE/RSJ Intern. Conf. on Intelligent Robots and Systems (IROS), St. Louis, USA (IEEE Press, 2009), pp. 2077–2082.

    Chapter  Google Scholar 

  16. L. Guo, F. M. Cardullo, J. A. Houck, et al., “New Predictive Filters for Compensating the Transport Delay on a Flight Simulator,” in Proc. of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Providence, USA, August 16–19, 2004, pp. 910–922.

  17. J. Kim, M.-S. Kang, and S. Park, “Accurate Modeling and Robust Hovering Control for a Quad-Rotor VTOL Aircraft,” J. Intell. Robotics Syst. 57(1–4), 9–26 (2010).

    Article  MATH  Google Scholar 

  18. S. Bouabdallah, “Design and Control of Quadrotors with Application to Autonomous Flying,” Ph.D. thesis (STI, Lausanne: EPFL, 2007).

    Google Scholar 

  19. R. E. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Trans. ASME J. Basic Eng. Ser. D, No. 82, 35–45 (1960).

    Google Scholar 

  20. G. Welch and G. Bishop, “An Introduction to the Kalman Filter,” Tech. Rep. (Chapel Hill, 1995).

    Google Scholar 

  21. Yu. N. Zolotukhin, K. YU. Kotov, A. S. Mal’tsev, et al., “Control of Trajectory Motion of a Group of Mobile Robots: Simulation and Experiment,” in Proc. X Intern. Conf. “Urgent Problems of Electronic Instrument Engineering,” Novosibirsk, Russia, 2010, pp. 101–106.

    Google Scholar 

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Correspondence to Yu. N. Zolotukhin.

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Original Russian Text © S.A. Belokon’, Yu.N. Zolotukhin, K.Yu. Kotov, A.S. Mal’tsev, A.A. Nesterov, V.Ya. Pivkin, M.A. Sobolev, M.N. Filippov, A.P. Yan, 2013, published in Avtometriya, 2013, Vol. 49, No. 6, pp. 14–24.

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Belokon’, S.A., Zolotukhin, Y.N., Kotov, K.Y. et al. Using the Kalman filter in the quadrotor vehicle trajectory tracking system. Optoelectron.Instrument.Proc. 49, 536–545 (2013). https://doi.org/10.3103/S8756699013060022

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  • DOI: https://doi.org/10.3103/S8756699013060022

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