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SCIENCE CHINA Information Sciences, Volume 63 , Issue 9 : 192206(2020) https://doi.org/10.1007/s11432-019-2671-y

Controlling the depth of a gliding robotic dolphin using dual motion control modes

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  • ReceivedJul 21, 2019
  • AcceptedSep 2, 2019
  • PublishedJul 24, 2020

Abstract

This paper investigates the performance of the dual mode, namely flipper mode and central pattern generator (CPG) mode, for controlling the depth of a gliding robotic dolphin. Subsequent to considering the errors in dynamic models, we propose a depth control system that combines the line-of-sight (LOS) method with an adaptive control approach (ACA) to deal with uncertainties in the model parameters. First, we establish a full-state dynamic model to conduct simulations and optimize the parameters used in later aquatic experiments. Then, we use the LOS method to transform the control target from the depth to the pitch angle and employ the ACA to calculate the control signal. In particular, we optimize the ACA's control parameters using simulations based on our dynamic model. Finally, our simulated and experimental results demonstrate not only that we can successfully control the robotic dolphin's depth, but also that its performance was better than that of the CPG-based control, thus indicating that we can achieve three-dimensional motion by combining flipper-based and CPG-based control. The results of this study suggest valuable ideas for practical applications of gliding robotic dolphins.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant Nos. 61421004, 61725305, 61633020, 61633017, 61603388) and Key Project of Frontier Science Research of Chinese Academy of Sciences (Grant No. QYZDJ-SSW-JSC004).


References

[1] Ijspeert A J. Biorobotics: Using robots to emulate and investigate agile locomotion. Science, 2014, 346: 196-203 CrossRef PubMed ADS Google Scholar

[2] Wu Z X, Yu J Z, Su Z S. Towards an Esox lucius inspired multimodal robotic fish. Sci China Inf Sci, 2015, 58: 1-13 CrossRef Google Scholar

[3] Yuan J, Yu J, Wu Z. Precise planar motion measurement of a swimming multi-joint robotic fish. Sci China Inf Sci, 2016, 59: 92208 CrossRef Google Scholar

[4] Zhang A, Ma S, Li B. Adaptive controller design for underwater snake robot with unmatched uncertainties. Sci China Inf Sci, 2016, 59: 052205 CrossRef Google Scholar

[5] Yu J, Li X, Pang L. Design and attitude control of a novel robotic jellyfish capable of 3D motion. Sci China Inf Sci, 2019, 62: 194201 CrossRef Google Scholar

[6] Liu J, Wu Z, Yu J. Sliding mode fuzzy control-based path-following control for a dolphin robot. Sci China Inf Sci, 2018, 61: 024201 CrossRef Google Scholar

[7] Nagai M. Thinking Fluid Dynamics with Dolphins. Tokyo: Ohmsha, 2002. Google Scholar

[8] Yu J, Su Z, Wang M. Control of Yaw and Pitch Maneuvers of a Multilink Dolphin Robot. IEEE Trans Robot, 2012, 28: 318-329 CrossRef Google Scholar

[9] Yu J, Su Z, Wu Z. An Integrative Control Method for Bio-Inspired Dolphin Leaping: Design and Experiments. IEEE Trans Ind Electron, 2016, 63: 3108-3116 CrossRef Google Scholar

[10] Eriksen C C, Osse T J, Light R D. Seaglider: a long-range autonomous underwater vehicle for oceanographic research. IEEE J Ocean Eng, 2001, 26: 424-436 CrossRef ADS Google Scholar

[11] Sherman J, Davis R E, Owens W B. The autonomous underwater glider “Spray”. IEEE J Ocean Eng, 2001, 26: 437-446 CrossRef ADS Google Scholar

[12] Webb D C, Simonetti P J, Jones C P. SLOCUM: an underwater glider propelled by environmental energy. IEEE J Ocean Eng, 2001, 26: 447-452 CrossRef ADS Google Scholar

[13] Leonard N E, Paley D A, Davis R E. Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey Bay. J Field Robotics, 2010, 27: 718-740 CrossRef Google Scholar

[14] Grasso R, Braca P, Fortunati S. Dynamic underwater glider network for environmental field estimation. IEEE Trans Aerosp Electron Syst, 2016, 52: 379-395 CrossRef ADS Google Scholar

[15] Wu Z X, Yu J Z, Yuan J, et al. Mechatronic design and implementation of a novel gliding robotic dolphin. In: Proceedings of IEEE International Conference on Robotics and Biomimetics, Zhuhai, 2015. 267--272. Google Scholar

[16] Wu Z, Yu J, Yuan J. Towards a Gliding Robotic Dolphin: Design, Modeling, and Experiments. IEEE/ASME Trans Mechatron, 2019, 24: 260-270 CrossRef Google Scholar

[17] Yuan J, Wu Z, Yu J. Sliding Mode Observer-Based Heading Control for a Gliding Robotic Dolphin. IEEE Trans Ind Electron, 2017, 64: 6815-6824 CrossRef Google Scholar

[18] Shen F, Cao Z Q, Zhou C, et al. Depth control for robotic dolphin based on fuzzy PID control. Int J Offshore Polar Eng, 2013, 23: 166--171. Google Scholar

[19] Ranganathan T, Singh V, Thondiyath A. Theoretical and Experimental Investigations on the Design of a Hybrid Depth Controller for a Standalone Variable Buoyancy System-vBuoy. IEEE J Ocean Eng, 2018, : 1-16 CrossRef Google Scholar

[20] Yu J, Liu J, Wu Z. Depth Control of a Bioinspired Robotic Dolphin Based on Sliding-Mode Fuzzy Control Method. IEEE Trans Ind Electron, 2018, 65: 2429-2438 CrossRef Google Scholar

[21] Yu J, Wang M, Tan M. Three-Dimensional Swimming. IEEE Robot Automat Mag, 2011, 18: 47-58 CrossRef Google Scholar

[22] Makrodimitris M, Aliprantis I, Papadopoulos E. Design and implementation of a low cost, pump-based, depth control of a small robotic fish. In: Proceedings of IEEE International Conference on Intelligent Robots and Systems, Chicago, 2014. 1127--1132. Google Scholar

[23] Yu J, Sun F, Xu D. Embedded Vision-Guided 3-D Tracking Control for Robotic Fish. IEEE Trans Ind Electron, 2016, 63: 355-363 CrossRef Google Scholar

[24] Wang J, Wu Z X, Yang Y Q, et al. Spiraling motion of a gliding robotic dolphin based on the 3-D dynamic model. In: Proceedings of IEEE International Conference on Real-time Computing and Robotics, Kandima, 2018. 13--18. Google Scholar

[25] Ijspeert A J, Crespi A, Ryczko D. From Swimming to Walking with a Salamander Robot Driven by a Spinal Cord Model. Science, 2007, 315: 1416-1420 CrossRef PubMed ADS Google Scholar

[26] Verma S, Shen D, Xu J X. Motion Control of Robotic Fish Under Dynamic Environmental Conditions Using Adaptive Control Approach. IEEE J Ocean Eng, 2018, 43: 381-390 CrossRef ADS Google Scholar

[27] Yu J, Yuan J, Wu Z. Data-Driven Dynamic Modeling for a Swimming Robotic Fish. IEEE Trans Ind Electron, 2016, 63: 5632-5640 CrossRef Google Scholar

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