Abstract
One of the most fundamental problems of rotary-wing aircraft that can take off and land vertically is that they cannot land safely when the ground on which they will land is too sloped. In case they have to make their landing, they inevitably face the risk of rolling over. The main source of this problem is that these vehicles have fixed landing gear. In this study, an important solution proposal is presented by performing an adaptive passive landing gear design and control for a four-rotor UAV with low takeoff weight, within the framework of the principle of fast adaptation to the ground, low cost, and weight. The experimental studies’ results indicated the usefulness of the proposed landing gear. This adaptive landing gear, produced within the scope of this study, has a total mass of 170 g, and it got the UAV to safely land on both sloped surfaces with 15 degrees and randomly uneven surfaces.
Similar content being viewed by others
Abbreviations
- \(\varphi\) :
-
Roll angle [°]
- \(\theta\) :
-
Pitch angle [°]
- \(\psi\) :
-
Yaw angle [°]
- [B]:
-
Body fixed frame
- [E]:
-
Earth fixed frame
- \({{}^{B}R}_{\mathrm{E}}\) :
-
Rotation matrix from the body frame to the earth frame
- \({M}_{\varphi }\) :
-
Roll moment [Nm]
- \({M}_{\theta }\) :
-
Pitch moment [Nm]
- \({M}_{\psi }\) :
-
Yaw moment [Nm]
- \({F}_{t}\) :
-
Total thrust force [N]
- \({\mathrm{F}}_{b}\) :
-
Acting on the fuselage of the UAV [N]
- \({\mathrm{F}}_{g}\) :
-
Gravitational force acting on the UAV [N]
- \({\mathrm{F}}_{d}\) :
-
Drag force [N]
- \(K\) :
-
Coefficient matrix
- \(m\) :
-
Mass of the UAV
- \(g\) :
-
Gravitational acceleration [\(\left[ {{\raise0.7ex\hbox{${\text{m}}$} \!\mathord{\left/ {\vphantom {{\text{m}} {{\text{s}}^{{\text{2}}} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${{\text{s}}^{{\text{2}}} }$}}} \right]\)]
- \({I}_{\mathrm{xx}}\) :
-
Moment of inertia in the x-axis of UAV [kg m2]
- \({I}_{\mathrm{yy}}\) :
-
Moment of inertia in the y-axis of UAV [kg m2]
- \({I}_{\mathrm{zz}}\) :
-
Moment of inertia in the z-axis of UAV [kg m2]
- \({J}_{\mathrm{r}}\) :
-
Moment of inertia of rotor [kg m2]
- \({\Omega }_{\mathrm{r}}\) :
-
Angular velocity vector of rotors
- \(l\) :
-
Distance between two opposing legs [m]
- \(d\) :
-
Maximum distance that one leg moves on the vertical axis [m]
- \(h\) :
-
Minimum distance between the center of gravity of the UAV and the ground [m]
- \({F}_{\mathrm{f}}\) :
-
Friction force [N]
- \({\mu }_{\mathrm{k}}\) :
-
Kinetic friction coefficient [-]
- \({\mu }_{\mathrm{s}}\) :
-
Static friction coefficient [-]
- \({m}_{\mathrm{l}}\) :
-
Mass of one leg [kg]
- \({F}_{\mathrm{f}\varphi }\) :
-
Roll axis component of friction force [N]
- \({F}_{\mathrm{f}\theta }\) :
-
Pitch axis component of friction force [N]
- \(\upgamma\) :
-
Critical angle of rolling over situations [°]
- \({I}_{0}\) :
-
Inertia of UAV around the center of mass [kg m2]
- ESC:
-
Electronic speed controller
- GPS:
-
Global positioning system
- EKF:
-
Extended Kalman filter
- PLA:
-
Polylactic acid
- ABS:
-
Acrylonitrile butadiene styrene
References
Yıldırım, Ş; Çabuk, N.; Bakırcıoğlu, V.: Modelling and control of proposed two dodecacopter systems. Int. J. Appl. Math. Electron. Comput. 8, 34–8 (2020). https://doi.org/10.18100/ijamec.698462
Bakırcıoğlu, V.; Çabuk, N.; Yıldırım, Ş: Experimental comparison of the effect of the number of redundant rotors on the fault tolerance performance for the proposed multilayer UAV. Rob. Auton. Syst. 149, 103977 (2022). https://doi.org/10.1016/j.robot.2021.103977
Verbeke, J.; Hulens, D.; Ramon, H.; Goedeme, T.; De Schutter, J.: The design and construction of a high endurance hexacopter suited for narrow corridors. In: 2014 international conference proceedings on unmanned aircraft systems ICUAS, 2014:543–51
Çabuk, N.; Yıldırım, Ş: Design, modelling and control of an eight-rotors UAV with asymmetric configuration for use in remote sensing systems. J. Aviat. 5, 72–81 (2021). https://doi.org/10.30518/jav.943804
Cardoso, D.N.; Esteban, S.; Raffo, G.V.: A new robust adaptive mixing control for trajectory tracking with improved forward flight of a tilt-rotor UAV. ISA Trans. 110, 86–104 (2021). https://doi.org/10.1016/j.isatra.2020.10.040
Heidari, H.; Saska, M.: Collision-free trajectory planning of multi-rotor UAVs in a wind condition based on modified potential field. Mech. Mach. Theory 156, 104140 (2021). https://doi.org/10.1016/j.mechmachtheory.2020.104140
Alkamachi, A.; Erçelebi, E.: Modelling and genetic algorithm based-PID control of H-shaped racing quadcopter. Arab. J. Sci. Eng. 42, 2777–2786 (2017). https://doi.org/10.1007/s13369-017-2433-2
Noordin, A.; Mohd Basri, M.A.; Mohamed, Z.; Mat, L.I.: Adaptive PID controller using sliding mode control approaches for quadrotor UAV attitude and position stabilization. Arab. J. Sci. Eng. 46, 963–981 (2021). https://doi.org/10.1007/s13369-020-04742-w
Tran, H.K.; Nguyen, T.N.: Flight motion controller design using genetic algorithm for a quadcopter. Meas. Control (United Kingdom) 51, 59–64 (2018). https://doi.org/10.1177/0020294018768744
Miranda-Colorado, R.; Aguilar, L.T.: Robust PID control of quadrotors with power reduction analysis. ISA Trans. 98, 47–62 (2020). https://doi.org/10.1016/j.isatra.2019.08.045
Zhang, B.; Xie, Y.; Zhou, J.; Wang, K.; Zhang, Z.: State-of-the-art robotic grippers, grasping and control strategies, as well as their applications in agricultural robots: a review. Comput. Electron. Agric. 177, 105694 (2020). https://doi.org/10.1016/j.compag.2020.105694
Ling, X.; Zhao, Y.; Gong, L.; Liu, C.; Wang, T.: Dual-arm cooperation and implementing for robotic harvesting tomato using binocular vision. Rob. Auton. Syst. 114, 134–143 (2019). https://doi.org/10.1016/j.robot.2019.01.019
Savsani, P.; Jhala, R.L.; Savsani, V.J.: Comparative study of different metaheuristics for the trajectory planning of a robotic arm. IEEE Syst. J. 10, 697–708 (2016). https://doi.org/10.1109/JSYST.2014.2342292
Liu, S.; Dong, W.; Ma, Z.; Sheng, X.: Adaptive aerial grasping and perching with dual elasticity combined suction cup. IEEE Robot. Autom. Lett. 5, 4766–4773 (2020). https://doi.org/10.1109/LRA.2020.3003879
McLaren, A.; Fitzgerald, Z.; Gao, G.; Liarokapis, M.: A passive closing, tendon driven, adaptive robot hand for ultra-fast, aerial grasping and perching. In: 2019 IEEE/RSJ international conference on intelligent robots systems, IEEE; 2019, p. 5602–7
Villa, D.K.D.; Brandão, A.S.; Sarcinelli-Filho, M.: A survey on load transportation using multirotor UAVs. J Intell. Robot. Syst. Theory Appl. 98, 267–296 (2020). https://doi.org/10.1007/s10846-019-01088-w
Bonyan Khamseh, H.; Janabi-Sharifi, F.; Abdessameud, A.: Aerial manipulation—a literature survey. Rob. Auton. Syst. 107, 221–235 (2018). https://doi.org/10.1016/j.robot.2018.06.012
Acosta, J.; de Cos, C.R.; Ollero, A.: Accurate control of aerial manipulators outdoors. A reliable and self-coordinated nonlinear approach. Aerosp. Sci. Technol. 99, 105731 (2020). https://doi.org/10.1016/j.ast.2020.105731
DARPA: Robotic landing gear could enable future helicopters to take off and land almost anywhere 2015. https://www.darpa.mil/news-events/2015-09-10 (Accessed June 7, 2021)
Bodie, K.; Tognon, M.; Siegwart, R.: Dynamic end effector tracking with an omnidirectional parallel aerial manipulator. IEEE Robot. Autom. Lett. 6, 8165–8172 (2021). https://doi.org/10.1109/LRA.2021.3101864
Ikura, M.; Miyashita, L.; Ishikawa, M.: Real-time landing gear control system based on adaptive 3D sensing for safe landing of UAV. In: Proceedings 2020 IEEE/SICE international symposium on system integration SII 2020 2020:759–64.
Çabuk, N.: Design and kinematic analysis of proposed adaptive landing gear for multirotor UAV. El-Cezeri J. Sci. Eng. 9, 159–70 (2022). https://doi.org/10.31202/ecjse.952728
Tang, H.; Zhang, D.; Tian, C.: An approach for modeling and performance analysis of three-leg landing gear mechanisms based on the virtual equivalent parallel mechanism. Mech. Mach. Theory 169, 104617 (2022). https://doi.org/10.1016/j.mechmachtheory.2021.104617
Tang, H.; Zhang, D.; Tian, C.: A method for comprehensive performance optimization of four-leg landing gear based on the virtual equivalent parallel mechanism. Mech. Mach. Theory 174, 104924 (2022). https://doi.org/10.1016/j.mechmachtheory.2022.104924
Hang, K.; Lyu, X.; Song, H.; Stork, J.A.; Dollar, A.M.; Kragic, D., et al.: Perching and resting-A paradigm for UAV maneuvering with modularized landing gears. Sci. Robot. (2019). https://doi.org/10.1126/scirobotics.aau6637
Ramon-Soria, P.; Gomez-Tamm, A.E.; Garcia-Rubiales, F.J.; Arrue, B.C.; Ollero, A.: Autonomous landing on pipes using soft gripper for inspection and maintenance in outdoor environments. In: 2019 IEEE/RSJ international conference on intelligent robots and systems, IEEE; 2019, p. 5832–9
Sarkisov, Y.S.; Yashin, G.A.; Tsykunov, E.V.; Tsetserukou, D.: DroneGear: a novel robotic landing gear with embedded optical torque sensors for safe multicopter landing on an uneven surface. IEEE Robot. Autom. Lett. 3, 1912–1917 (2018). https://doi.org/10.1109/LRA.2018.2806080
Nadan, P.M.; Anthony, T.M.; Michael, D.M.; Pflueger, J.B.; Sethi, M.S.; Shimazu, K.N., et al.: A bird-inspired perching landing gear system. J. Mech. Robot. (2019). https://doi.org/10.1115/1.4044416
Tang, H.; Zhang, D.; Gan, Z.: Control system for vertical take-off and landing vehicle’s adaptive landing based on multi-sensor data fusion. Sensors (Switzerland) 20, 1–21 (2020). https://doi.org/10.3390/s20164411
Yashin, G.; Egorov, A.; Darush, Z.; Zherdev, N.; Tsetserukou, D.: LocoGear: locomotion analysis of robotic landing gear for multicopters. IEEE J. Miniaturizat. Air Sp. Syst. 1, 138–147 (2020). https://doi.org/10.1109/jmass.2020.3015525
Choi, J.; Cheon, D.; Lee, J.: Robust landing control of a quadcopter on a slanted surface. Int. J. Precis. Eng. Manuf. 22, 1147–1156 (2021). https://doi.org/10.1007/s12541-021-00523-z
Ikura, M.; Miyashita, L.; Ishikawa, M.: Stabilization system for UAV landing on rough ground by adaptive 3d sensing and high-speed landing gear adjustment. J. Robot. Mechatr. 33, 108–18 (2021). https://doi.org/10.20965/jrm.2021.p0108
Liu, J.; Zhang, D.; Wu, C.; Tang, H.; Tian, C.: A multi-finger robot system for adaptive landing gear and aerial manipulation. Rob. Auton. Syst. (2021). https://doi.org/10.1016/j.robot.2021.103878
Paul, H.; Miyazaki, R.; Ladig, R.; Shimonomura, K.: TAMS: development of a multipurpose three-arm aerial manipulator system. Adv. Robot. 35, 31–47 (2021). https://doi.org/10.1080/01691864.2020.1845237
Liu, J.; Zhang, D.; Chen, Y.; Xia, Z.; Wu, C.: Design of a class of generalized parallel mechanisms for adaptive landing and aerial manipulation. Mech. Mach. Theory (2022). https://doi.org/10.1016/j.mechmachtheory.2021.104692
Paul, H.; Miyazaki, R.; Kominami, T.; Ladig, R.; Shimonomura, K.: A versatile aerial manipulator design and realization of uav take-off from a rocking unstable surface. Appl. Sci. (2021). https://doi.org/10.3390/app11199157
Luo, C.; Zhao, W.; Du, Z.; Yu, L.: A neural network based landing method for an unmanned aerial vehicle with soft landing gears. Appl. Sci. (2019). https://doi.org/10.3390/app9152976
Yıldırım, Ş; Çabuk, N.; Bakırcıoğlu, V.: Comparison of flight performances of unmanned air vehicle with six rotors and eight rotors under different disturbance effects. Konya J. Eng. Sci. 8, 552–62 (2020). https://doi.org/10.36306/konjes.594701
Oktay, T.; Köse, O.: Dynamic modeling and simulation of quadrotor for different flight conditions. Eur. J. Sci. Technol. (2019). https://doi.org/10.31590/ejosat.507222
Yıldırım, Ş; Çabuk, N.; Bakırcıoğlu, V.: Design and trajectory control of universal drone system. Measurement 147, 106834 (2019). https://doi.org/10.1016/j.measurement.2019.07.062
Jiang, F.; Pourpanah, F.; Hao, Q.: Design, implementation, and evaluation of a neural-network-based quadcopter UAV system. IEEE Trans. Ind. Electron. 67, 2076–2085 (2020). https://doi.org/10.1109/TIE.2019.2905808
Maleki Roudposhti, M.; Haghzad, K.S.: Development of a novel wheeled parallel robot with six degrees of freedom. Arab. J. Sci. Eng. (2022). https://doi.org/10.1007/s13369-022-06950-y
Debnath, D.; Malla, P.; Roy, S.: Position control of a DC servo motor using various controllers: a comparative study. Mater. Today Proc. 58, 484–488 (2022). https://doi.org/10.1016/j.matpr.2022.03.008
Zheng, X.; Li, J.; Wang, Q.; Liao, Q.: A methodology for modeling and simulating frictional translational clearance joint in multibody systems including a flexible slider part. Mech. Mach. Theory 142, 103603 (2019). https://doi.org/10.1016/j.mechmachtheory.2019.103603
Marques, F.; Woliński, Ł; Wojtyra, M.; Flores, P.; Lankarani, H.M.: An investigation of a novel LuGre-based friction force model. Mech. Mach. Theory (2021). https://doi.org/10.1016/j.mechmachtheory.2021.104493
Lee, T.H.; Tan, K.K.; Huang, S.: Adaptive friction compensation with a dynamical friction model. IEEE/ASME Trans. Mechatr. 16, 133–140 (2011)
Tian, Y.; Huo, Z.; Wang, F.; Liang, C.; Shi, B.; Zhang, D.: A novel friction-actuated 2-DOF high precision positioning stage with hybrid decoupling structure. Mech. Mach. Theory 167, 104511 (2022). https://doi.org/10.1016/j.mechmachtheory.2021.104511
Alzaher, H.A.; Alghamdi, M.K.: An all-digital low-noise switching DC–DC buck converter based on a multi-sampling frequency delta-sigma modulation with enhanced light-load efficiency. Arab. J. Sci. Eng. 45, 1411–1419 (2020). https://doi.org/10.1007/s13369-019-03955-y
Ebeid, E.; Skriver, M.; Terkildsen, K.H.; Jensen, K.; Schultz, U.P.: A survey of open-source UAV flight controllers and flight simulators. Microprocess. Microsyst. 61, 11–20 (2018). https://doi.org/10.1016/j.micpro.2018.05.002
Yang, B.; Yang, E.; Yu, L.; Niu, C.: Adaptive extended Kalman filter-based fusion approach for high-precision UAV positioning in extremely confined environments. IEEE/ASME Trans. Mechatr. (2022). https://doi.org/10.1109/TMECH.2022.3203875
Author information
Authors and Affiliations
Corresponding author
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary file1 (MP4 9011 kb)
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Çabuk, N. Design and Experimental Validation of an Adaptive Landing Gear for Safe Landing on Uneven Grounds of VTOL UAVs in the Context of Lightweight and Fast Adaptations. Arab J Sci Eng 48, 12331–12344 (2023). https://doi.org/10.1007/s13369-023-07731-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13369-023-07731-x