Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-27T18:52:57.388Z Has data issue: false hasContentIssue false

Autonomous landing of a quadrotor on a moving platform using vision-based FOFPID control

Published online by Cambridge University Press:  20 September 2021

Ali Ghasemi*
Affiliation:
Department of Mechanical Engineering, Faculty of Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
Farhad Parivash
Affiliation:
Mechanical and Mechatronics Engineering Department, Shahrood University of Technology, Shahrood, Iran
Serajeddin Ebrahimian
Affiliation:
Mechatronics Engineering Department, Faculty of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
*
*Corresponding author. E-mail: [email protected]

Abstract

This research deals with the autonomous landing maneuver of a quadrotor unmanned aerial vehicle (UAV) on an unmanned ground vehicle (UGV). It is assumed that the UGV moves independently, and there is no communication and collaboration between the two vehicles. This paper aims at the design of a closed-loop vision-based control system for quadrotor UAV to perform autonomous landing maneuvers in the possible minimum time despite the wind-induced disturbance force. In this way, a fractional-order fuzzy proportional-integral-derivative controller is introduced for the nonlinear under-actuated system of a quadrotor. Also, a feedback linearization term is included in the control law to compensate model nonlinearities. A supervisory control algorithm is proposed as an autonomous landing path generator to perform fast, smooth, and accurate landings. On the other hand, a compound AprilTag fiducial marker is employed as the target of a vision positioning system, enabling high precision relative positioning in the range between 10 and 350 cm height. A software-in-the-loop simulation testbed is realized on the windows platform. Numerical simulations with the proposed control system are carried out, while the quadrotor system is exposed to different disturbance conditions and actuator dynamics with saturated thrust output are considered.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bae, H. W. and Fahimi, F., “A single-loop MIMO trajectory tracking controller for autonomous quadrotors: The control point concept,” Robotica 39(3), 438451 (2021).CrossRefGoogle Scholar
Villanueva, A., Luque-Vega, L. F., González-Jiménez, L. E. and Arellano-Muro, C. A., “Robust multimode flight framework based on sliding mode control for a rotary UAV,” Robotica 39(4), 699717 (2021).CrossRefGoogle Scholar
Valavanis, K. P. and Vachtsevanos, G. J., Handbook of Unmanned Aerial Vehicles (Springer, Dordrecht, The Netherlands, 2015) pp. 29933009.CrossRefGoogle Scholar
Raj, R. and Murray, C., “The multiple flying sidekicks traveling salesman problem with variable drone speeds,” Transp. Res. C Emer. Technol. 120, 102813 (2020).CrossRefGoogle Scholar
Baniasadi, P., Foumani, M., Smith-Miles, K. and Ejov, V., “A transformation technique for the clustered generalized traveling salesman problem with applications to logistics,” Eur. J. Oper. Res. 285(2), 444457 (2020).CrossRefGoogle Scholar
Voos, H. and Bou-Ammar, H., “Nonlinear Tracking and Landing Controller for Quadrotor Aerial Robots,” In: 2010 IEEE International Conference on Control Applications IEEE (2010, September) pp. 2136–2141.CrossRefGoogle Scholar
Herisse, B., Hamel, T., Mahony, R. and Russotto, F. X., “The Landing Problem of a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow,” In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems IEEE (2010, October) pp. 16001605.CrossRefGoogle Scholar
Daly, J. M., Ma, Y. and Waslander, S. L., “Coordinated landing of a quadrotor on a skidsteered ground vehicle in the presence of time delays,” Autonom. Robots 38(2), 179191 (2015).CrossRefGoogle Scholar
Benavidez, P. J., Lambert, J., Jaimes, A. and Jamshidi, M., “Landing of a Quadcopter on a Mobile Base Using Fuzzy Logic,” In: Advance Trends in Soft Computing (Springer, Cham, 2014) pp. 429437.Google Scholar
Lee, D., Ryan, T. and Kim, H. J., “Autonomous Landing of a VTOL UAV on a Moving Platform Using Image-Based Visual Servoing,” In: 2012 IEEE International Conference on Robotics and Automation (2012, May, IEEE) pp. 971976.CrossRefGoogle Scholar
Serra, P., Cunha, R., Hamel, T., Cabecinhas, D. and Silvestre, C., “Landing of a quadrotor on a moving target using dynamic image-based visual servo control,” IEEE Transactions on Robotics, 32(6), 15241535 (2016).CrossRefGoogle Scholar
Olivares-Mendez, M. A., Kannan, S. and Voos, H., “Vision Based Fuzzy Control Autonomous Landing with UAVs: From V-REP to Real Experiments,” In: 2015 23rd Mediterranean Conference on Control and Automation (MED) (2015, June, IEEE) pp. 14–21.CrossRefGoogle Scholar
Ghommam, J. and Saad, M., “Autonomous landing of a quadrotor on a moving platform,” IEEE Trans. Aerosp. Electron. Syst. 53(3), 15041519 (2017).CrossRefGoogle Scholar
Wenzel, K. E., Masselli, A. and Zell, A., “Automatic take off, tracking and landing of a miniature UAV on a moving carrier vehicle,” J. Intell. Robot. Syst. 61(1–4), 221238 (2011).CrossRefGoogle Scholar
Bi, Y. and Duan, H., “Implementation of autonomous visual tracking and landing for a lowcost quadrotor,” Optik-Int. J. Light Electron Opt. 124(18), 32963300 (2013).CrossRefGoogle Scholar
Kim, J., Jung, Y., Lee, D. and Shim, D. H., “Outdoor Autonomous Landing on a Moving Platform for Quadrotors Using an Omnidirectional Camera,” In: 2014 International Conference on Unmanned Aircraft Systems (ICUAS) (2014, May. IEEE) pp. 1243–1252.Google Scholar
Lange, S., Sunderhauf, N. and Protzel, P., “A Vision Based Onboard Approach for Landing and Position Control of an Autonomous Multirotor UAV in GPS-Denied Environments,” In: 2009 International Conference on Advanced Robotics (2009, June. IEEE) pp. 16.Google Scholar
Yang, S., Ying, J., Lu, Y. and Li, Z., “Precise Quadrotor Autonomous Landing with SRUKF Vision Perception,” In: 2015 IEEE International Conference on Robotics and Automation (ICRA) (2015, May. IEEE) pp. 2196–2201.Google Scholar
Olson, E., “AprilTag: A Robust and Flexible Visual Fiducial System,” In: 2011 IEEE International Conference on Robotics and Automation (2011, May. IEEE) pp. 34003407.CrossRefGoogle Scholar
Borowczyk, A., Nguyen, D. T., Phu-Van Nguyen, A., Nguyen, D. Q., Saussié, D. and Le Ny, J.. Autonomous landing of a multirotor micro air vehicle on a high velocity ground vehicle. IFAC-PapersOnLine 50(1), 1048810494 (2017).CrossRefGoogle Scholar
Wang, Z., She, H. and Si, W., “Autonomous Landing of Multi-Rotors UAV with Monocular Gimbaled Camera on Moving Vehicle,” In: 2017 13th IEEE International Conference on Control & Automation (ICCA) (2017, July. IEEE) pp. 408–412.CrossRefGoogle Scholar
Almeshal, A. M. and Alenezi, M. R., “A vision-based neural network controller for the autonomous landing of a quadrotor on moving targets,” Robotics 7(4), 71 (2018).CrossRefGoogle Scholar
Hu, B. and Mishra, S., “Time-optimal trajectory generation for landing a quadrotor onto a moving platform,” IEEE/ASME Trans. Mechatron. 24(2), 585596 (2019).CrossRefGoogle Scholar
Rodriguez-Ramos, A., Sampedro, C., Bavle, H., De La Puente, P. and Campoy, P., “A deep reinforcement learning strategy for UAV autonomous landing on a moving platform,” J. Intell. Robot. Syst. 93(1–2), 351366 (2019).CrossRefGoogle Scholar
Qi, Y., Jiang, J., Wu, J., Wang, J., Wang, C. and Shan, J., “Autonomous landing solution of low-cost quadrotor on a moving platform,” Robot. Autonom. Syst. 119, 6476 (2019).CrossRefGoogle Scholar
Bhargavapuri, M., Shastry, A. K., Sinha, H., Sahoo, S. R. and Kothari, M., “Vision-based autonomous tracking and landing of a fully-actuated rotorcraft,” Cont. Eng. Pract. 89, 113129 (2019).CrossRefGoogle Scholar
Heidari, H. and Saska, M., “Trajectory planning of quadrotor systems for various objective functions,” Robotica 39(1), 137152 (2021).CrossRefGoogle Scholar
Polvara, R., Sharma, S., Wan, J., Manning, A. and Sutton, R., “Autonomous vehicular landings on the deck of an unmanned surface vehicle using deep reinforcement learning,” Robotica 37(11), 18671882 (2019).CrossRefGoogle Scholar
Kayacan, E. and Maslim, R., “Type-2 fuzzy logic trajectory tracking control of quadrotor VTOL aircraft with elliptic membership functions,” IEEE/ASME Trans. Mechatron. 22(1), 339348 (2017).CrossRefGoogle Scholar
Parivash, F. and Ghasemi, A., “Trajectory Tracking Control for a Quadrotor Using Fuzzy PID Control Scheme,” In: 2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI) (IEEE, 2017) pp. 0553–0558.CrossRefGoogle Scholar
Gottwald, S., Fuzzy Sets and Fuzzy Logic: The Foundations of Application—From A Mathematical Point of View (Springer-Verlag, 2013).Google Scholar
Niemiec, M., Fuzzy Inference System: Theory and Applications (Scitus Academics LLC, 2016).Google Scholar
Parivash, F. and Ghasemi, A., “Trajectory tracking control of quadrotor using fractional-order fuzzy PID controller in the presence of wind disturbance,” Modares Mech. Eng. 18(8), 4554 (2018).Google Scholar
Sharma, R., Rana, K. P. S. and Kumar, V., “Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator,” Exp. Syst. Appl. 41(9), 42744289 (2014).CrossRefGoogle Scholar
Corke, P., Robotics. Vision and Control (2011).CrossRefGoogle Scholar
Marchand, É., Spindler, F. and Chaumette, F., “ViSP for visual servoing: A generic software platform with a wide class of robot control skills,” IEEE Robot. Automat. Mag. 12(4), 4052 (2005).CrossRefGoogle Scholar