Finite state machine and ultrasonic ranging-based approach for automatic grasping by aerial manipulator
Aerospace Systems - Trang 1-10 - 2024
Tóm tắt
This paper introduces an experiment-based recognition and grasping control method for aerial manipulators. The method consists of two parts: an automatic grasping process using a finite state machine, and an ultrasonic ranging principle. The D–H parameter method is utilized for analyzing the manipulator’s degree of freedoms, equipped with bus servos controlled via serial communication. The proposed strategy is evaluated using a practical experiment of the aerial manipulator system. This research contributes to the field of aerial manipulators by providing a robust and flexible way of grasping targets.
Tài liệu tham khảo
Yang B, He Y, Han J (2015) Survey on aerial manipulator systems. Robot. https://doi.org/10.13973/j.cnki.robot.2015.0628
Setty K, van Niekerk T, Stopforth R (2020) Generic gripper for an unmanned aerial vehicle[J]. Proc. CIRP 91:486–488. https://doi.org/10.1016/j.procir.2020.02.203
Liu CH, Chiu CH, Hsu MC et al (2019) Topology and size-shape optimization of an adaptive compliant gripper with high mechanical advantage for grasping irregular objects[J]. Robotica 37(8):1383–1400. https://doi.org/10.1017/S0263574719000018
Erbil MA, Prior SD, Keane AJ (2013) Design optimisation of a reconfigurable perching element for vertical take-off and landing unmanned aerial vehicles[J]. Int J Micro Air Vehicles 5(3):207–228. https://doi.org/10.1260/1756-8293.5.3.207
Ruggiero F, Trujillo M A, Cano R, et al. A multilayer control for multirotor UAVs equipped with a servo robot arm[C]//2015 IEEE international conference on robotics and automation (ICRA). IEEE, 2015: 4014-4020. doi:10.1109/ICRA.2015.7139760
Zhang G, He Y, Dai B et al (2018) Towards grasping task: System and control of an aerial manipulator[J]. Robot 40(6):1–11. https://doi.org/10.13973/j.cnki.robot.180127
Dydek Zachary T, Annaswamy Anuradha M, Lavretsky Eugene (2012) Adaptive control of quadrotor UAVs: A design trade study with flight evaluations. IEEE Trans Control Syst Technol 21(4):1400–1406. https://doi.org/10.1109/TCST.2012.2200104
Lee H, Kim HJ (2016) Estimation, control, and planning for autonomous aerial transportation[J]. IEEE Trans Indus Electron 64(4):3369–3379. https://doi.org/10.1109/TIE.2016.2598321
Lee Hyeonbeom, Jin Kim H (2017) Constraint-based cooperative control of multiple aerial manipulators for handling an unknown payload. IEEE Trans Indus Inform 13:2780–2790
Muscio Giuseppe et al (2017) Coordinated control of aerial robotic manipulators: Theory and experiments. IEEE Trans Control Syst Technol 26:1406–1413. https://doi.org/10.1109/TCST.2017.2716905
Khalifa Ahmed, Fanni Mohamed, Toru Namerikawa MPC, DOb-based robust optimal control of a new quadrotor manipulation system. (2016) European Control Conference (ECC). IEEE 2016. https://doi.org/10.1109/ECC.2016.7810331
Pounds PEI, Bersak DR, Dollar AM (2012) Stability of small-scale UAV helicopters and quadrotors with added payload mass under PID control. Auton Robots 33(1/2):129–142
de Araujo, Vitor, et al. A parallel hierarchical finite state machine approach to UAV control for search and rescue tasks. 2014 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO). Vol. 1. IEEE, 2014. doi:10.5220/0005121104100415
Kügler Martin E, Holzapfel Florian, Autoland for a novel UAV as a state-machine-based extension to a modular automatic flight guidance and control system. (2017) American Control Conference (ACC). IEEE 2017. https://doi.org/10.23919/ACC.2017.7963284
Fabresse Felipe R, Localization and mapping for aerial manipulation based on range-only measurements and visual markers. et al (2014) IEEE international conference on robotics and automation (ICRA). IEEE 2014. https://doi.org/10.1109/ICRA.2014.6907147
Watson Robert et al (2021) Dry coupled ultrasonic non-destructive evaluation using an over-actuated unmanned aerial vehicle. IEEE Trans Autom Sci Eng 19:2874–2889. https://doi.org/10.1109/TASE.2021.3094966
Patil A, Kulkarni M, Aswale A. Analysis of the inverse kinematics for 5 DOF robot arm using DH parameters[C]//2017 IEEE International Conference on Real-time Computing and Robotics (RCAR). IEEE, 2017: 688-693. https://doi.org/10.1109/RCAR.2017.8311944
Quillen D, Jang E, Nachum O, et al. Deep reinforcement learning for vision-based robotic grasping: A simulated comparative evaluation of off-policy methods[C]//2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018: 6284-6291. https://doi.org/10.1109/ICRA.2018.8461039
Chebotar Y, Handa A, Makoviychuk V, et al. Closing the sim-to-real loop: Adapting simulation randomization with real world experience[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 8973-8979. https://doi.org/10.1109/ICRA.2019.8793789
James S, Abbeel P. Coarse-to-fine Q-Attention with learned path ranking[J]. arXiv preprint arXiv:2204.01571, 2022. https://doi.org/10.48550/arXiv.2204.01571