Abstract
The manta ray robot switches the state of its pectoral fins to achieve different swimming states. In this paper, we propose a control method for pectoral fin flutter based on the central pattern generator (CPG). The pectoral fin state is determined by the amplitude, frequency, and phase difference of the CPG output signal. Momentary manipulation of the phase signal output from the CPG can produce a spike or interruption, which leads to unstable pectoral fin flutter of the manta ray robot. Too slow a phase transition can make the response slower and reduce the maneuverability of the robot. An optimization method for the phase transition of the manta ray robot’s pectoral fin state is investigated. With the output signal smoothness and rapidity as the optimization objectives, the Nondominated Sorting Genetic Algorithm-II (NSAG-II) is used to optimize the CPG parameters and obtain the optimal parameter combination. It is verified by simulation and experiment that the optimized CPG controller output signal can transition smoothly and quickly during phase switching.
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References
Fish, F.E., Hoffman, J.L.: Stability design and response to waves by batoids. Integr. Comp. Biol. 55(4), 648–661 (2015)
Zhang, D., Pan, G., Cao, Y., Huang, Q., Cao, Y.: A novel integrated gliding and flapping propulsion biomimetic manta-ray robot. J. Mar. Sci. Eng. 10(7), 924 (2022)
Ames, B., Morgan, J., Konidaris, G.: Ikflow: generating diverse inverse kinematics solutions. IEEE Robot. Autom. Lett. 7(3), 7177–7184 (2022)
He, W., Chen, Y., Yin, Z.: Adaptive neural network control of an uncertain robot with full-state constraints. IEEE Trans. Cybern. 46(3), 620–629 (2015)
Wang, M., Li, X., Zhang, Y., Chang, Z., Yu, J.: Locomotion control of robotic fish with a hierarchical framework combining spiking neural networks and CPGs. In: 2019 IEEE 9th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), pp. 1187–1190. IEEE, Suzhou (2019)
Cao, Y., Xie, Y., He, Y., Pan, G., Huang, Q., Cao, Y.: Bioinspired central pattern generator and TS fuzzy neural network-based control of a robotic manta for depth and heading tracking. J. Mar. Sci. Eng. 10(6), 758 (2022)
Ijspeert, A.J.: Central pattern generators for locomotion control in animals and robots: a review. Neural Netw. 21(4), 642–653 (2008)
Zhou, C., Low, K.H.: Design and locomotion control of a biomimetic underwater vehicle with fin propulsion. IEEE/ASME Trans. Mechatron. 17(1), 25–35 (2011)
Ikeda, M., Hikasa, S., Watanabe, K., Nagai, I.: A CPG design of considering the attitude for the propulsion control of a Manta robot. In: IECON 2013–39th Annual Conference of the IEEE Industrial Electronics Society, pp. 6354–6358. IEEE, Austria (2013)
Cao, Y., Ma, S., Cao, Y., Pan, G., Huang, Q., Cao, Y.: Similarity evaluation rule and motion posture optimization for a manta ray robot. J. Mar. Sci. Eng. 10(7), 908 (2022)
Hao, Y., Cao, Y., Cao, Y., Huang, Q., Pan, G.: Course Control of a manta robot based on amplitude and phase differences. J. Mar. Sci. Eng. 10(2), 285 (2022)
Qiao, G., Wen, X., Lin, J., Wang, D., Wei, Z.: Sigmoid transition approach of the central pattern generator-based controller for the snake-like robot. Int. J. Adv. Rob. Syst. 14(3), 1729881417705289 (2017)
Takeda, K., Torikai, H.: Smooth gait transition in hardware-efficient CPG model based on asynchronous coupling of cellular automaton phase oscillators. Nonlinear Theory Appl. IEICE 12(3), 336–355 (2021)
Li, X., Wang, W., Yi, J.: Gait transition based on CPG modulation for quadruped locomotion. In 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pp. 500–505. IEEE, Busan (2015)
Nor, N.M., Ma, S.: Smooth transition for CPG-based body shape control of a snake-like robot. Bioinspir. Biomim. 9(1), 016003 (2013)
Yusoff, Y., Ngadiman, M.S., Zain, A.M.: Overview of NSGA-II for optimizing machining process parameters. Procedia Eng. 15, 3978–3983 (2011)
Gunantara, N.: A review of multi-objective optimization: methods and its applications. Cogent Eng. 5(1), 1502242 (2018)
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Ma, S. et al. (2023). NSGA-II Optimization-Based CPG Phase Transition Control Method of Manta Ray Robot. In: Sun, F., Cangelosi, A., Zhang, J., Yu, Y., Liu, H., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2022. Communications in Computer and Information Science, vol 1787. Springer, Singapore. https://doi.org/10.1007/978-981-99-0617-8_34
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DOI: https://doi.org/10.1007/978-981-99-0617-8_34
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