CPG Motion Control for a Bionic Manta Ray Robot Fish Propelled by Flexible Pectoral Fin
-
摘要: 文中以蝠鲼为仿生对象, 提出了一种基于柔性胸鳍推进的仿蝠鲼机器鱼设计方案, 并针对该机器鱼设计了基于中枢模式发生器(CPG)的运动控制策略, 进行了控制参数的影响分析与多种运动模态的性能测试。首先, 对蝠鲼的运动特征进行了分析, 在实际仿生功能需求下提出了仿蝠鲼机器鱼的整体设计方案。然后, 为实现仿蝠鲼机器鱼在不同游动模式下的稳定游动及连续平稳切换, 设计了一种CPG运动控制方法, 并分析了各控制参数对CPG拓扑网络结构输出信号的影响。最后, 对仿蝠鲼机器鱼的机动性进行了进一步的游动测试, 验证了仿蝠鲼机器鱼能在水下灵活实现直线巡游、转向及浮潜等多种运动模态, 具有出色的运动性能和应用前景。Abstract: Considering a manta ray as the bionic object, this paper proposes a design scheme for a bionic manta-ray robot fish with flexible pectoral fin propulsion. A motion control strategy is designed based on a central pattern generator(CPG), the influence of control parameters is analyzed, and the performance of multiple motion modes is tested. First, the movement characteristics of the manta ray are analyzed, and an overall design scheme for the bionic manta ray robotic fish is proposed under the actual bionic function requirements. Then, to realize continuous and stable swimming of the bionic manta-ray robot fish in different swimming modes, a CPG motion control method is designed, and the influence of the control parameters is analyzed for the output signals of the designed CPG topology network structure. Finally, a further swimming test is conducted on the maneuverability of the bionic manta-ray robotic fish; the results verified that the bionic manta-ray robotic fish can flexibly realize various motion modes such as linear cruise, steering, floating, and diving, and therefore, it has excellent motion performance and application prospects.
-
表 1 直线巡游模式下CPG拓扑网络参数取值
Table 1. Parameter value of CPG topological network in linear cruise mode
参数 取值 参数 取值 fi [1, 1, 1] Ai [60, 60, k] φij 0 Bi [0, 0, 0] 表 2 同类型仿蝠鲼机器鱼对比
Table 2. Comparison of same type biomic manta ray robotic fish
表 3 转向模式下CPG拓扑网络参数取值
Table 3. Parameter value of CPG topological network in steering mode
参数 取值 参数 取值 fi [1,1.2,1] Ai [60,60,30] φij 0 Bi [0,0,0] 表 4 原地旋转模式下CPG拓扑网络参数取值
Table 4. Parameter value of CPG topological network in local rotation mode
参数 取值 参数 取值 fi [0, 1.2, 1] Ai [0, 60, 30] φij 0 Bi [0, 0, 0] 表 5 浮潜游动模式下CPG拓扑网络参数取值
Table 5. Parameter value of CPG topological network in floating and diving motion mode
参数 取值 参数 取值 fi [1, 1, 1] Ai [60, 60, 60] φij 0 Bi [0, 0, ±30] -
[1] 范增, 王扬威, 刘凯, 等. 仿生机器鱼胸鳍波动与摆动融合推进机制建模及实验研究[J]. 水下无人系统学报, 2019, 27(2): 166-173.Fan Zeng, Wang Yangwei, Liu Kai, et al. Modeling and experimental research of integrating propulsion mechanism of pectoral fin’s fluctuation and swing for the biomimetic robotic fish[J]. Journal of Unmanned Undersea Systems, 2019, 27(2): 166-173. [2] Breder C M. The locomotion of fishes[J]. Zoologica, 1926, 4: 159-297. [3] Xiong G, Lauder G V. Center of mass motion in swimming fish: effects of speed and locomotor mode during undulatory propulsion[J]. Zoology, 2014, 117(4): 269-281. doi: 10.1016/j.zool.2014.03.002 [4] 王田苗, 杨兴帮, 梁建宏. 中央鳍/对鳍推进模式的仿生自主水下机器人发展现状综述[J]. 机器人, 2013, 35(3): 352-362. doi: 10.3724/SP.J.1218.2013.00352 [5] 胡举喜, 吴均云, 田忠殿. 胸鳍推进仿生无人潜航器研究浅析[C]//鳌山论坛·2019 年水下无人系统技术高峰论坛论文集. 青岛: 《水下无人系统学报》编辑部, 2019. [6] Liu G, Ren Y, Zhu J, et al. Thrust producing mechanisms in ray-inspired underwater vehicle propulsion[J]. Theoretical and Applied Mechanics Letters, 2015, 5(1): 54-57. doi: 10.1016/j.taml.2014.12.004 [7] Moored K W, Smith W, Hester J M, et al. Investigating the thrust production of a myliobatoid-inspired oscillating wing[J]. Advances in Science and Technology, 2008, 58: 25-30. [8] 盛兆华, 杨朔. 仿鳐鱼水下航行器动态流体仿真[J]. 水下无人系统学报, 2021, 29(3): 308-312. [9] Zhou C, Low K H. Better endurance and load capacity: an improved design of manta ray robot: RoMan-Ⅱ[J]. Journal of Bionic Engineering, 2010, 7(3): 137-144. [10] 李吉, 毕树生, 高俊, 等. 仿生蝠鲼机器鱼BH-RAY3的研制及水力实验[J]. 控制工程, 2010, 17(1): 127-130. [11] Gao J, Bi S, Xu Y, et al. Development and design of a robotic manta ray featuring flexible pectoral fins[C]//IEEE International Conference on Robotics and Biomimetics. Sanya: IEEE, 2008: 519-523. [12] Chew C M, Arastehfar S, Gunawan G, et al. Study of sweep angle effect on thrust generation of oscillatory pectoral fins[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS). Vancouver, BC, Canada: IEEE, 2017. [13] 和岩辉, 胡桥, 王朝晖, 等. 基于CPG和模糊控制的机器鱼定向游动精确控制方法[J]. 水下无人系统学报, 2021, 29(1): 39-47.He Yanhui, Hu Qiao, Wang Chaohui, et al. Precise control method for directional swimming of a robotic fish based on CPG and fuzzy control[J]. Journal of Unmanned Undersea Systems, 2021, 29(1): 39-47. [14] Matsuoka K. Mechanisms of frequency and pattern control in the neural rhythm generators[J]. 1987, 56(5-6): 345-353. [15] Shi R, Zhang X, Tian Y, et al. A CPG-based control method for the rolling locomotion of a desert spider[C]//Advanced Robotics & Its Social Impacts. Shanghai, China: IEEE, 2016. [16] 汪明, 喻俊志, 谭民. 胸鳍推进型机器鱼的CPG控制及实现[J]. 机器人, 2010, 32(2): 248-255. doi: 10.13973/j.cnki.robot.2010.02.018 [17] Zhou C, Low K H. On-line optimization of biomimetic undulatory swimming by an experiment-based approach[J]. Journal of Bionic Engineering, 2014, 11(2): 213-225. doi: 10.1016/S1672-6529(14)60042-1 [18] Ijspeert A J, Crespi A, Ryczko D, et al. From swimming to walking with a salamander robot driven by a spinal cord model[J]. Science, 2007, 315(5817): 1416-1420. doi: 10.1126/science.1138353 [19] Chen L, Qiao T, Bi S, et al. Modeling and simulation research on soft pectoral fin of a bionic robot fish inspired by manta ray[J]. Journal of Mechanical Engineering, 2020, 56(19): 182. doi: 10.3901/JME.2020.19.182 [20] 牛传猛, 毕树生, 蔡月日, 等. 胸鳍摆动推进仿生鱼的设计及水动力实验[J]. 机器人, 2014, 36(5): 535-543.