Bottom-level motion control for robotic fish to swim in groups: modeling and experiments

Li Liang; Liu Anquan; Wang Wei; Ravi Sridhar; Fu Rubin; Yu Junzhi; Xie Guangming

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Bottom-level motion control for robotic fish to swim in groups: modeling and experiments

机译：机器人鱼类游泳的底层运动控制：建模与实验

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Moving in groups is an amazing spectacle of collective behaviour in fish and has attracted considerable interest from many fields, including biology, physics and engineering. Although robotic fish have been well studied, including algorithms to simulate group swimming, experiments that demonstrate multiple robotic fish as a stable group are yet to be achieved. One of the challenges is the lack of a robust bottom-level motion control system for robotic fish platforms. Here we seek to overcome this challenge by focusing on the design and implementation of a motion controller for robotic fish that allows multiple individuals to swim in groups. As direction control is essential in motion control, we first propose a high-accuracy controller which can control a sub-carangiform robotic fish from one arbitrary position/pose (position and direction) to another. We then develop a hydrodynamic-model-based simulation platform to expedite the process of the parameter tuning of the controller. The accuracy of the simulation platform was assessed by comparing the results from experiments on a robotic fish using speeding and turning tests. Subsequently, extensive simulations and experiments with robotic fish were used to verify the accuracy and robustness of the bottom-level motion control. Finally, we demonstrate the efficacy of our controller by implementing group swimming using three robotic fish swimming freely in prescribed trajectories. Although the fluid environment can be complex during group swimming, our bottom-level motion control remained nominally accurate and robust. This motion control strategy lays a solid foundation for further studies of group swimming with multiple robotic fish.

机译：进入团体是鱼类中集体行为的惊人奇观，吸引了许多领域的相当兴趣，包括生物学，物理和工程。虽然机器人鱼已经很好地研究，包括模拟群体游泳的算法，但尚未实现作为稳定组的多种机器人鱼的实验。其中一个挑战是为机器人钓鱼平台缺乏强大的底层运动控制系统。在这里，我们寻求通过专注于机器人鱼类的设计和实施来克服这一挑战，允许多个人在群体中游泳。随着方向控制在运动控制中是必不可少的，我们首先提出了一种高精度控制器，它可以控制从一个任意位置/姿势/姿势（位置和方向）到另一个的亚碳状机器人鱼。然后，我们开发基于流体动力学模型的仿真平台，以加快控制器参数调谐的过程。通过使用超速和转动测试将结果与机器人鱼类的实验比较来评估模拟平台的准确性。随后，使用机器人鱼类的广泛模拟和实验验证了底层运动控制的准确性和鲁棒性。最后，我们通过在规定的轨迹中自由游泳的三个机器人鱼类来展示我们的控制器的功效。虽然流体环境在小组游泳期间可以复杂，但我们的底层运动控制仍然是标称准确和鲁棒的。该运动控制策略为进一步研究进行了多种机器人鱼类，为进一步研究进行了坚实的基础。

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来源
《Bioinspiration & biomimetics》 |2019年第4期|共14页
作者
Li Liang; Liu Anquan; Wang Wei; Ravi Sridhar; Fu Rubin; Yu Junzhi; Xie Guangming;
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作者单位

Peking Univ Coll Engn State Key Lab Turbulence &

Complex Syst Beijing 0087 Peoples R China;

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

Peking Univ Coll Engn State Key Lab Turbulence &

Complex Syst Beijing 0087 Peoples R China;

Univ New South Wales Sch Engn &

Informat Technol Australian Def Force Acad Canberra ACT Australia;

Peking Univ Coll Engn State Key Lab Turbulence &

Complex Syst Beijing 0087 Peoples R China;

Chinese Acad Sci Inst Automat State Key Lab Management &

Control Complex Syst Beijing 100190 Peoples R China;

Peking Univ Coll Engn State Key Lab Turbulence &

Complex Syst Beijing 0087 Peoples R China;

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原文格式 PDF
正文语种 eng
中图分类生物工程学（生物技术）;
关键词
robotic fish; hydrodynamic model; group swimming; motion control;

机译：机器人鱼;流体动力学模型;小组游泳;运动控制;

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专利

1. Bottom-level motion control for robotic fish to swim in groups: modeling and experiments [J] . Li Liang, Liu Anquan, Wang Wei, Bioinspiration & biomimetics . 2019,第4期

机译：机器人鱼类游泳的底层运动控制：建模与实验
2. Real-Time Feedback-Controlled Robotic Fish for Behavioral Experiments With Fish Schools [J] . Swain D. T., Couzin I. D., Ehrich Leonard N. Proceedings of the IEEE . 2012,第1期

机译：鱼类学校行为实验的实时反馈控制机器人鱼
3. Mechatronic design and locomotion control of a robotic thunniform swimmer for fast cruising [J] . Hu Yonghui, Liang Jianhong, Wang Tianmiao Bioinspiration & biomimetics . 2015,第2期

机译：用于快速巡航的机器人菱形游泳者的机电一体化设计和运动控制
4. A Methodology of Modelling Fish-like Swim Patterns for Robotic Fish [C] . Liu, Jindong, Hu, . 2007

机译：机器人鱼的鱼状游泳模式建模方法
5. Kinematics and hydrodynamics of undulatory locomotion in hagfishes (Myxinidae) and hagfish-like robotic models [D] . Lim, Jeanette Li Li 2013

机译：海草（骨髓苷）和豹状机械模型过度运动的运动学和流体动力学
6. Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems [O] . Olatunji Mumini Omisore, Shipeng Han, Yousef Al-Handarish, 2020

机译：柔性手术机器人系统的运动和轨迹约束控制建模
7. Development of a Bio-inspired Vision System for Mobile Micro-robots:In this paper, we present a new bio-inspired vision system for mobile micro-robots. The processing method takes inspiration from vision of locusts in detecting the fast approaching objects. Research suggested that locusts use wide-field visual neuron called the lobula giant movement detector to respond to imminent collisions. We employed the locusts' vision mechanism to motion control of a mobile robot. The selected image processing method is implemented on a developed extension module using a low-cost and fast ARM processor. The vision module is placed on top of a micro-robot to control its trajectory and to avoid obstacles. The observed results from several performed experiments demonstrated that the developed extension module and the inspired vision system are feasible to employ as a vision module for obstacle avoidance and motion control. [O] . Hu, Cheng, Arvin, Farshad, Yue, Shigang 2014

机译：开发用于移动微型机器人的生物启发视觉系统：在本文中，我们提出了一种用于移动微型机器人的新型生物启发视觉系统。该处理方法从检测快速接近物体的蝗虫视觉中获取灵感。研究表明，蝗虫使用称为小叶巨型运动探测器的宽视野神经元来应对即将发生的碰撞。我们采用蝗虫的视觉机制来控制移动机器人。所选择的图像处理方法使用低成本且快速的aRm处理器在开发的扩展模块上实现。视觉模块放置在微型机器人的顶部以控制其轨迹并避开障碍物。几次进行的实验观察到的结果表明，开发的扩展模块和灵感视觉系统可用作避障和运动控制的视觉模块。

Bottom-level motion control for robotic fish to swim in groups: modeling and experiments

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