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Autonomous unmanned aerial vehicle flight accuracy evaluation for three different path-tracking algorithms

    Ramūnas Kikutis Affiliation
    ; Jonas Stankūnas Affiliation
    ; Darius Rudinskas Affiliation

Abstract

This paper shows mathematical results of three methods, which can be used for Unmanned Aerial Vehicle (UAV) to make transition from one flight leg to another. In paper, we present general equations, which can be used for generating waypoint-switching methods when for experiment purpose mathematical UAV model is used. UAV is modelled as moving dot, which eliminates all of the aerodynamics factors and we can concentrate only on the navigation problems. Lots of attention is dedicated to show possible flight path error values with representation of modelled flight path trajectories and deviations from the flight mission path. All of the modelled flight missions are done in two-dimensional space and all the results are evaluated by looking at Probability Density Function (PDF) values, as we are mostly interested in the probability of the error.

Keyword : navigation, Dubins paths, waypoint-switching method, flight path error, unmanned aerial vehicle, dynamic model

How to Cite
Kikutis, R., Stankūnas, J., & Rudinskas, D. (2019). Autonomous unmanned aerial vehicle flight accuracy evaluation for three different path-tracking algorithms. Transport, 34(6), 652-661. https://doi.org/10.3846/transport.2019.11741
Published in Issue
Dec 19, 2019
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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Ariff, O. K.; Go, T. H. 2011. Waypoint navigation of small-scale UAV incorporating dynamic soaring, The Journal of Navigation 64(1): 29–44. https://doi.org/10.1017/s0373463310000378

Avellar, G. S. C.; Pereira, G. A. S.; Pimenta, L. C. A.; Iscold, P. 2015. Multi-UAV routing for area coverage and remote sensing with minimum time, Sensors 15(11): 27783–27803. https://doi.org/10.3390/s151127783

Beard, R. W.; Humpherys, J. 2011. Following straight line and orbital paths with input constraints, Proceedings of the 2011 American Control Conference, 29 June–1 July 2011, San Francisco, CA, US, 1587–1592. https://doi.org/10.1109/acc.2011.5990840

Benghezal, A.; Louali, R.; Bazoula, A.; Chettibi, T. 2015. Trajectory generation for a fixed-wing UAV by the potential field method, in 2015 3rd International Conference on Control, Engineering & Information Technology (CEIT), 25–27 May 2015, Tlemcen, Algeria, 1–6. https://doi.org/10.1109/CEIT.2015.7233049

Brezoescu, A.; Castillo, P.; Lozano, R. 2011. Straight-line path following in windy conditions, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 38(1/C22): 283–288. https://doi.org/10.5194/isprsarchives-xxxviii-1-c22-283-2011

Capello, E.; Guglieri, G.; Quagliotti, F. B. 2009. UAVs and simulation: an experience on MAVs, Aircraft Engineering and Aerospace Technology 81(1): 38–50. https://doi.org/10.1108/00022660910926890

Capello, E.; Guglieri, G.; Ristorto, G. 2017. Guidance and control algorithms for mini UAV autopilots, Aircraft Engineering and Aerospace Technology 89(1): 133–144. https://doi.org/10.1108/aeat-10-2014-0161

Casbeer, D. W.; Kingston, D. B.; Beard, R. W.; McLain, T. W. 2006. Cooperative forest fire surveillance using a team of small unmanned air vehicles, International Journal of Systems Science 37(6): 351–360. https://doi.org/10.1080/00207720500438480

Chamseddine, A.; Zhang, Y.; Rabbath, C. A.; Theilliol, D. 2012. Trajectory planning and replanning strategies applied to a quadrotor unmanned aerial vehicle, Journal of Guidance, Control, and Dynamics 35(5): 1667–1671. https://doi.org/10.2514/1.56606

Dadkhah, N.; Mettler, B. 2012. Survey of motion planning literature in the presence of uncertainty: considerations for UAV guidance, Journal of Intelligent & Robotic Systems 65(1–4): 233–246. https://doi.org/10.1007/s10846-011-9642-9

Kothari, M.; Postlethwaite, I.; Gu, D.-W. 2014. UAV path following in windy urban environments, Journal of Intelligent & Robotic Systems 74(3–4): 1013–1028. https://doi.org/10.1007/s10846-013-9873-z

Li, W.; Chen, W.; Wang, C.; Liu, M.; Ge, Y.; Song, Q. 2015. A 3D path planning approach for quadrotor UAV navigation, in 2015 IEEE International Conference on Information and Automation, 8–10 August 2015, Lijiang, China, 2481–2486. https://doi.org/10.1109/icinfa.2015.7279703

Maillot, T.; Boscain, U.; Gauthier, J.-P.; Serres, U. 2015. Lyapunov and minimum-time path planning for drones, Journal of Dynamical and Control Systems 21(1): 47–80. https://doi.org/10.1007/s10883-014-9222-y

Nelson, D. R.; Barber, D. B.; McLain, T. W.; Beard, R. W. 2006. Vector field path following for small unmanned air vehicles, in 2006 American Control Conference, 14–16 June 2016, Minneapolis, MN, US, 5788–5794. https://doi.org/10.1109/acc.2006.1657648

Owen, M.; Beard, R. W.; McLain, T. W. 2015. Implementing Dubins airplane paths on fixed-wing UAVs, in K. Valavanis, G. Vachtsevanos (Eds.). Handbook of Unmanned Aerial Vehicles, 1677–1701. https://doi.org/10.1007/978-90-481-9707-1_120

Stojcsics, D. 2014. Autonomous waypoint-based guidance methods for small size unmanned aerial vehicles, Acta Polytechnica Hungarica 11(10): 215–233.

Wang, T.; Le Maître, O. P.; Hoteit, I.; Knio, O. M. 2016. Path planning in uncertain flow fields using ensemble method, Ocean Dynamics 66(10): 1231–1251. https://doi.org/10.1007/s10236-016-0979-2

Yeol, J. W.; Hwang, Y.-W. 2016. Parametrization of nonlinear trajectory for time optimal 2D path planning for unmanned aerial vehicles, in 2016 2nd International Conference on Control, Automation and Robotics (ICCAR), 28–30 April 2016, Hong Kong, China, 335–339. https://doi.org/10.1109/iccar.2016.7486751

Zhong, W.; Yan, L. 2014. A target visiting path planning algorithm for the fixed-wing UAV in obstacle environment, in Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference, 8–10 August 2014, Yantai, China, 2774–2778. https://doi.org/10.1109/CGNCC.2014.7007603