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Three-dimensional guidance and control for ground moving target tracking by a quadrotor

Published online by Cambridge University Press:  29 April 2021

M. Sepehri Movafegh
Affiliation:
Graduated from Control and Intelligent Systems Department School of Electrical and Computer Engineering University of TehranTehranIran
S.M.M. Dehghan*
Affiliation:
Faculty of Electrical and Computer Engineering Malek Ashtar University of TechnologyTehranIran
R. Zardashti
Affiliation:
Faculty of Aerospace Malek Ashtar University of TechnologyTehranIran

Abstract

This paper develops a three-dimensional guidance and control algorithm to ensure that a manoeuverable target is preserved by a quadrotor in a long-term tracking scenario. The proposed guidance approach determines the desired altitude of the quadrotor to adjust the field of view (FOV) to the union of two desired trusted and critical regions. The dimensions of the desired trusted region depend on the controller performance that is evaluated by the distance of the target from the center of the FOV. The critical region is a predefined margin around the trusted region that is defined by the operator based on the upper bounds of the quadrotor and target localisation errors. It also depends on the duration and magnitude of the temporal increase in the target velocity compared to the quadrotor velocity. A sufficient condition is provided for the minimum desired altitude of the quadrotor to ensure that the target is maintained in the FOV. Furthermore, a model predictive control (MPC) is employed to preserve the target at the center of the aerial image and the desired altitude determined by the guidance law. Also, the integrals of the position errors are used to achieve null steady-state errors in the presence of wind disturbances. The simulation results show the effectiveness of the proposed approach in preserving the manoeuverable target in the FOV in the presence of the wind, the uncertainty of the target and quadrotor localisation, accelerations estimation errors, and terrain altitude variation.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

Gomez-Balderas, J.E., Flores, G., Carrillo, L.R.G. and Lozano, R. Tracking a ground moving target with a quadrotor using switching control, J. Intell. Robot. Syst., 2013, 70, (1), pp 6578.CrossRefGoogle Scholar
Gans, N.R., Nagarajan, G., Hu, K. and Dixon, W.E. Keeping multiple moving targets in the field of view of a mobile camera, IEEE Trans. Rob., 2011, 27, (4), pp 822828.10.1109/TRO.2011.2158695CrossRefGoogle Scholar
Zhu, S., Wang, D. and Low, C.B. Ground target tracking using UAV with input constraints, J. Intell. Robot. Syst., 2012, 69, pp 417429.10.1007/s10846-012-9737-yCrossRefGoogle Scholar
Kim, D. and Hong, S.K. Target pointing and circling of a region of interest with quadcopter, Int. J. Appl. Eng. Res., 2016, 11, (2), pp 10821088.Google Scholar
Abbasi, E. and Mahjoob, M. Quadrotor UAV guidance for ground moving target tracking, J. Adv. Comput. Eng. Technol., 2016, 2, (1), pp 3744.Google Scholar
Ghamry, K.A., Dong, Y., Kame, M.A. and Zhang, Y. Real-time autonomous take-off, tracking and landing of UAV on a moving UGV platform, 24th Mediterranean Conference on Control and Automation, 2016, pp 12361241.CrossRefGoogle Scholar
Engelhardt, T., Konrad, T., Schafer, B. and Abel, D. Flatness-based control for a quadrotor camera helicopter using model predictive control trajectory generation, 24th Mediterranean Conference on Control and Automation, 2016, pp 852859.CrossRefGoogle Scholar
Tan, R. and Kumar, M. Tracking of ground mobile targets by quadrotor unmanned aerial vehicles, Unmanned Syst., 2014, 2, pp 157173.CrossRefGoogle Scholar
Prevost, C., Theriault, O., Desbiens, A., Poulin, E. and Gagnon, E. Receding horizon model-based predictive control for dynamic target tracking: a comparative study, AIAA Guidance, Navigation, and Control Conference, 2009, pp 62–68.10.2514/6.2009-6268CrossRefGoogle Scholar
Chen, J., Liu, T. and Shen, S. Tracking a moving target in cluttered environments using a quadrotor, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016, pp 446453.Google Scholar
Kim, S., Oh, H. and Tsourdos, A. Nonlinear model predictive coordinated standoff tracking of a moving ground vehicle, J. Guidance Control Dyn., 2013, 36, (2), pp 557566.CrossRefGoogle Scholar
Oh, H., Kim, S., Shin, H.S., White, B.A., Tsourdos, A. and Rabbath, A. Rendezvous and standoff target tracking guidance using differential geometry, J. Intell. Rob. Syst., 2013, 69, 389405.10.1007/s10846-012-9751-0CrossRefGoogle Scholar
Liu, X., Yang, Y., Ma, C., Li, J. and Zhang, S. Real-time visual tracking of moving targets using a low-cost unmanned aerial vehicle with a 3-axis stabilized gimbal system, J. Appl. Sci., 2020, 10, 5064. doi: 10.3390/app10155064.CrossRefGoogle Scholar
Yang, X., Zhu, R., Wang, J. and Li, Z. Real-time object tracking via least squares transformation in spatial and Fourier domains for unmanned aerial vehicles, Chin. J. Aeronaut., 2019, 32, (7), pp 17161726.10.1016/j.cja.2019.01.020CrossRefGoogle Scholar
Dong, F., You, K. and Zhang, J. Flight control for UAV loitering over a ground target with unknown maneuver, IEEE Trans. Control Syst. Technol., 2019, 28, (6), 24612473.CrossRefGoogle Scholar
Liang, X., Chen, G., Zhao, S. and Xiu, Y. Moving target tracking method for unmanned aerial vehicle/unmanned ground vehicle heterogeneous system based on AprilTag, J. Meas. Control, 2020, 53, (3–4), pp 427440.CrossRefGoogle Scholar
Esposito, N., Fontana, U., D’Autilia, G. and Bianchi, L. A hybrid approach to detection and tracking of unmanned aerial vehicles, AIAA J., 2020. https://doi.org/10.2514/6.2020-1345.CrossRefGoogle Scholar
Costelo, M.F. Theory of the Analysis of Rotorcraft Operation in Atmospheric Turbulence, PhD thesis, Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, May 1992.Google Scholar
Raffo, G.V., Ortega, M.G. and Rubio, F.R. An integral predictive/nonlinear control structure for a quadrotor helicopter, Automatica, 2010, 46, pp 2939.CrossRefGoogle Scholar
Yang, X., Pota, H. and Garratt, M. Design of a gust-attenuation controller for landing operations of un-manned autonomous helicopters, 2009 IEEE Control Applications, (CCA) Intelligent Control, (ISIC), 2009, pp. 1300–1305.10.1109/CCA.2009.5281074CrossRefGoogle Scholar
Pflimlin, J.M., Soueres, P. and Hamel, T. Position control of a ducted fan VTOL UAV in crosswind, Int. J. Control, 2007, 80, 666683.CrossRefGoogle Scholar
Cheviron, T., Plestan, F. and Chriette, A. Position control of a ducted fan VTOL UAV in crosswind, Int. J. Control, 2009, 82, pp 22062220.10.1080/00207170902948043CrossRefGoogle Scholar
Waslander, S., Hoffmann, G., Jang, J.S. and Tomlin, C. Multi-agent quadrotor testbed control design: integral sliding mode vs. reinforcement learning, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005. (IROS 2005), 2005, pp 37123717.CrossRefGoogle Scholar
Alexis, K., Nikolakopoulos, G. and Tzes, A. On trajectory tracking model predictive control of an unmanned quadrotor helicopter subject to aerodynamic disturbances, Asian. J. Control, 2014, 16, pp 209224.10.1002/asjc.587CrossRefGoogle Scholar
Bouabdallah, S. and Siegwart, R. Full control of a quadrotor, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007, 2007, pp 153158.10.1109/IROS.2007.4399042CrossRefGoogle Scholar
Sunan, T.K.K.H. and Heng, L.T. Applied Predictive Control, Springer-Verlag, 2002, New York, ch 3.Google Scholar
Camacho, E. and Bordons, C. Model Predictive Control, Springer-Verlag, 2007, New York, ch 2.Google Scholar