Abstract
Underwater autonomous manipulation is a challenging task, which not only includes a complicated multibody dynamic and hydrodynamic process, but also involves the limited observation environment. This study systematically investigates the dynamic modeling and control of the underwater vehicle-manipulator multibody system. The dynamic model of underwater vehicle-manipulator system has been established on the basis of the Newton–Euler recursive algorithm. On the basis of dynamic analysis, a motion planning optimization algorithm has been designed in order to realize the coordinate motions between AUV and manipulator through reducing the restoring forces and saving the electric power. On the other hand, a disturbance force observer including the coupling and restoring forces has been designed. An observer-based dynamic control scheme has been established in combination with kinematic and dynamic controller. Furthermore, from the simulations, although the disturbance forces such as restoring and coupling forces are time varying and great, the observer-based dynamic coordinate controller can maintain the AUV attitude stable during the manipulator swing and pitch motions. During the precise manipulation simulation, the stable AUV attitude and minimization of disturbance forces have been realized through combination of optimal motion planning and the observer-based dynamic coordinate controller.
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Kim, T.W., Yuh, J.: Development of a real-time control architecture for a semi-autonomous underwater vehicle for intervention missions. Control Eng. Pract. 12(12), 1521–1530 (2004)
Santhakumar, M.: Proportional-derivative observer-based backstepping control for an underwater manipulator. Math. Probl. Eng. 4, 1–18 (2011)
Lewandowski, C., Akin, D., Dillow, B.: Development of a deep-sea robotic manipulator for autonomous sampling and retrieval. In: Proceedings of 2008 IEEE/OES Autonomous Underwater Vehicles, Woods Hole, MA United States, 13–14 October, pp. 1–6 (2008)
Prats, M., Garcia, J.C., Fernandez, J.J.: Advances in the specification and execution of underwater autonomous manipulation tasks. In: Proceedings of OCEANS 2011 IEEE, Santander, Spain, 6–9 June, pp. 1–5 (2011)
Huang, H., Tang, Q., Li, Y., Wan, L., Pang, Y.: Dynamic control and disturbance estimation of 3D path-following for the observation class underwater remotely operated vehicle. Adv. Mech. Eng. 5(12), 604393 (2015)
Wroock, P., Frey, C.: Deep-sea AUV navigation using side-scan sonar images and SLAM. In: Proceedings of OCEANS’10 IEEE Sydney, NSW, Australia, 24–27 May, pp. 1–8 (2010)
Prats, M., Ribas, D., Palomeras, N.: Reconfigurable AUV for intervention missions: a case study on underwater object recovery. Intell. Serv. Robot. 5(1), 19–31 (2012)
Morales, R., Sira-Ramírez, H., Somolinos, J.A.: Robust control of underactuated wheeled mobile manipulators using GPI disturbance observers. Multibody Syst. Dyn. 32(4), 1–23 (2014)
Xu, W., Meng, D., Chen, Y., Qian, H., Xu, Y.: Dynamics modeling and analysis of a flexible-base space robot for capturing large flexible spacecraft. Multibody Syst. Dyn. 32(3), 357–401 (2013)
White, G.D., Bhatt, R.M., Krovi, V.N.: Dynamic redundancy resolution in a nonholonomic wheeled mobile manipulator. Robotica 25(2), 147–156 (2007)
Fossen, T.I.: Handbook of Marine Craft Hydrodynamics and Motion Control. Wiley, New York (2011)
Antonelli, G.: Underwater Robots Motion and Force Control of Vehicle-Manipulator Systems. Springer, Berlin/Heidelberg (2003)
Padois, V., Fourquet, J.Y., Chiron, P.: Kinematic and dynamic model-based control of wheeled mobile manipulators: a unified framework for reactive approaches. Robotica 25(2), 157–173 (2007)
From, P.J., Duindam, V., Pettersen, K.Y., Gravdahl, J.T., Sastry, S.: Singularity-free dynamic equations of vehicle-manipulator systems. Simul. Model. Pract. Theory 18(6), 712–731 (2010)
Mohan, A., Saha, S.K.: A recursive, numerically stable and efficient simulation algorithm for serial robots. Multibody Syst. Dyn. 17(4), 291–319 (2007)
Oki, T., Nakanishi, H., Yoshida, K.: Time-optimal manipulator control for management of angular momentum distribution during the capture of a tumbling target. Adv. Robot. 24(24), 441–466 (2010)
Xu, W., Liang, B., Xu, Y.: Survey of modeling, planning, and ground verification of space robotic systems. Acta Astronaut. 68(68), 1629–1649 (2011)
Tan, X., Zhao, D., Yi, J., Xu, D.: Adaptive hybrid control for omnidirectional mobile manipulators using neural-network. In: Proceedings of American Control Conference Westin Seattle Hotel, Seattle, Washington DC, USA, 11–13 June, pp. 5174–5179 (2008)
Li, Z., Yang, Y., Li, J.: Adaptive motion/force control of mobile under-actuated manipulators with dynamics uncertainties by dynamic coupling and output feedback. IEEE Trans. Control Syst. Technol. 18(5), 1068–1079 (2010)
Zhang, W., Ye, X., Jiang, L., Zhu, Y., Ji, X., Hu, X.: Output feedback control for free-floating space robotic manipulators base on adaptive fuzzy neural-network. Aerosp. Sci. Technol. 29(1), 135–143 (2013)
Chu, Z., Sun, F., Cui, J.: Disturbance Observer-based robust control of free-floating space manipulators. IEEE Syst. J. 2(1), 114–119 (2008)
Mahesh, H., Yuh, J., Lakshmi, R.: A coordinated control of an underwater vehicle and robot manipulator. J. Robot. Syst. 8(3), 339–370 (1991)
Podder, T.K.: Motion planning of autonomous underwater vehicle-manipulator systems. Ph.D. Dissertation (2000)
Sarkar, N., Podder, T.K.: Coordinated motion planning and control of autonomous underwater vehicle-manipulator systems subject to drag optimization. IEEE J. Ocean. Eng. 26(2), 228–239 (2001)
Enrico, S., Giuseppe, C., Sandro, T., Alessandro, S., Alessio, T.: Floating underwater manipulation: developed control methodology and experimental validation within the TRIDENT project. J. Field Robot. 31(3), 364–385 (2014)
Ismail, Z.H., Dunnigan, M.W.: Redundancy resolution for underwater vehicle-manipulator systems with congruent gravity and buoyancy loading optimization. In: Proceedings of International Conference on Robotics & Biomimetics, Guilin, China, 19–23 December, pp. 1393–1399 (2009)
Han, J., Chung, W.: Active use of restoring moments for motion control of an underwater vehicle-manipulator system. IEEE J. Ocean. Eng. 39(1), 100–109 (2014)
Mohan, S., Kim, J.: Indirect adaptive control of an autonomous underwater vehicle-manipulator system for underwater manipulation tasks. Ocean Eng. 54(4), 233–243 (2012)
Han, J., Park, J., Chung, W.: Robust coordinated motion control of an underwater vehicle-manipulator system with minimizing restoring moments. Ocean Eng. 38(10), 1197–1206 (2011)
Tsai, C., Cheng, M., Lin, S.: Dynamic modeling and tracking control of a nonholonomic wheeled mobile manipulator with dual arms. J. Intell. Robot. Syst. 47(4), 317–340 (2006)
Tsai, L.: Robot Analysis. Wiley, New York (1999)
Stokey, R., Austin, T., Allen, B., Forrester, N., Gifford, E., Goldsborough, R., Packard, G.: Very shallow water mine countermeasures using the REMUS AUV: a practical approach yielding accurate results. In: Proceedings of Oceans 2001 MTS/IEEE Conference. Honolulu,HI, United States, 5–8 November pp. 149–156 (2001)
Acknowledgements
This work is supported by the National Science Foundation of China (No. 51209050; No. 51579053; No. 61633009), the preresearch fund of State Key of Science and Technology of Underwater Vehicle (No. 9140C270306130C27102), the State Key Laboratory of Robotics and Systems at Harbin Institute of Technology (No. SKLRS-2012-ZD-03 and No. SKLRS-2015-ZD-03). Meanwhile, this work is also partially supported by the Fundamental Research Funds for the Central Universities (No. 2014KJ032), and the “Interdisciplinary Project” (No. 20153683) and “The Youth 1000” Program. It is also sponsored by “Shanghai Pujiang Program” (No. 15PJ1408400) and funded by the Key Basic Research Project of “Shanghai Science and Technology Innovation Plan” (No. 15JC1403300). All these supports are highly appreciated.
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Huang, H., Tang, Q., Li, H. et al. Vehicle-manipulator system dynamic modeling and control for underwater autonomous manipulation. Multibody Syst Dyn 41, 125–147 (2017). https://doi.org/10.1007/s11044-016-9538-3
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DOI: https://doi.org/10.1007/s11044-016-9538-3