基于CFD的仿鲹科机器鱼动力学建模与运动控制

仿生机器鱼的运动控制是仿生机器鱼推广应用的基础;然而,仿鲹科机器鱼的推进一般采用鱼体波数据,很少采用真实鱼类游动数据;为了深入探究仿鲹科机器鱼运动控制方法,采用了计算流体力学方法,通过标定流体介质、来流速度、鱼体几何形状等措施,利用Fluent软件进行了建模,然后针对鱼体波数据和真实金枪鱼游动采样数据两种不同推进数据对仿生机器鱼进行了仿真和实验;结果表明对于多关节仿生机器鱼推进方面,真实金枪鱼游动采样数据相较于常见的鱼体波产生的推进数据,在躯干进行大幅值摆动的情况下效果更好;这一仿真和实验对比为仿鲹科机器鱼的高效运动控制提供了一种新思路。     

Bio-harmonized control experiments of a carangiform robotic fish underwater vehicle

This paper presents experimental implementation and comparison of three different control schemes of a bio-inspired robotic fish underwater vehicle. The dynamics model is obtained by unifying conventional rigid body dynamics and bio-fluid dynamics of a carangiform fish swimming given by Lighthill’s(LH) slender body theory. It proposes an inclusive mathematical design for better control and energy efficient path travel for the robotic fish. The system is modeled as an two-link robot manipulator (caudal tail) with a mobile base (head). This forward thrust drives the robotic fish head represented by a combined non-linear equation of motion in earth fixed frame. We develop and compare the dynamic motion closed loop control strategy of the bio-harmonized robotic fish based on three different non-linear control schemes using CTM (Computed Torque Method), FF (Feed-Forward) controllers both with dynamic PD compensation and finally a proposed combination of CTM with FF. An inverse dynamic control method based on non-linear state function model including hydrodynamics is proposed to improve tracking performance. CTM control generates a feedback loop for linearization and decoupling robot dynamic model with a shorter response time, while a dynamic PD compensation in the FF path is employed by FF scheme through the desired trajectories. FF model-based strategy results in an improved tracking and shorter route to travel between two points. Overall results indicate that performances of the proposed control schemes based on the inverse dynamic model are comparable and useful for robotic fish motion tracking in fluid environment.     

Development of a biomimetic robotic fish and its control algorithm

This paper is concerned with the design of a robotic fish and its motion control algorithms. A radio-controlled, four-link biomimetic robotic fish is developed using a flexible posterior body and an oscillating foil as a propeller. The swimming speed of the robotic fish is adjusted by modulating joint's oscillating frequency, and its orientation is tuned by different joint's deflections. Since the motion control of a robotic fish involves both hydrodynamics of the fluid environment and dynamics of the robot, it is very difficult to establish a precise mathematical model employing purely analytical methods. Therefore, the fish's motion control task is decomposed into two control systems. The online speed control implements a hybrid control strategy and a proportional-integral-derivative (PID) control algorithm. The orientation control system is based on a fuzzy logic controller. In our experiments, a point-to-point (PTP) control algorithm is implemented and an overhead vision system is adopted to provide real-time visual feedback. The experimental results confirm the effectiveness of the proposed algorithms.     

仿生机器鱼运动学模型优化与实验

以仿生学为基础的机器鱼是一种新型水下机器人,具有高速、高效、节能等方面优势。为进一步探索仿生机器鱼的运动机理,指出了当前仿生机器鱼运动学模型存在的不足,即未考虑因制造、鱼体结构的影响,而产生的头部左右摆动。故在考虑仿生机器鱼头部摆动的情况下,构建头部摆动方程,引入摆动偏移量,修正其运动学模型。利用MATLAB对模型进行优化,分析结果表明修正后的运动学模型更能够描述实体仿生机器鱼的游动特性。最后,将修正后的运动学模型,运用到三关节仿生机器鱼上进行实验,结果表明,该模型能够有效地抑制仿生机器鱼头部摆动,进而提高了仿生机器鱼的游动速度。     

A 3D simulator for autonomous robotic fish

This paper presents a 3D simulator used for studying the motion control and autonomous navigation of robotic fish. The simulator's system structure and computation flow are presented. Simplified kinematics and hydrodynamics models for a virtual robotic fish are proposed. Many other object models are created for water, obstacles, sonar sensors and a swimming pool. Experimental results show that the simulator provides a, realistic and convenient way to develop autonomous navigation algorithms for robotic fish.     

Precise planar motion measurement of a swimming multi-joint robotic fish一种面向多关节机器鱼平面运动的精确测量方法

This paper presents a method for planar motion measurement of a swimming multi-joint robotic fish. The motion of the robotic fish is captured via image sequences and a proposed tracking scheme is employed to continuously detect and track the robotic fish. The tracking scheme initially acquires a rough scope of the robotic fish and thereafter precisely locates it. Historical motion information is utilized to determine the rough scope, which can speed up the tracking process and avoid possible ambient interference. A combination of adaptive bilateral filtering and k-means clustering is then applied to segment out color markers accurately. The pose of the robotic fish is calculated in accordance with the centers of these markers. Further, we address the problem of time synchronization between the on-board motion control system of the robotic fish and the motion measurement system. To the best of our knowledge, this problem has not been tackled in previous research on robotic fish. With information about both the multi-link structure and motion law of the robotic fish, we convert the problem to a nonlinear optimization problem, which we then solve using the particle swarm optimization (PSO) algorithm. Further, smoothing splines are adopted to fit curves of poses versus time, in order to obtain a continuous motion state and alleviate the impact of noise. Velocity is acquired via a temporal derivative operation. The results of experiments conducted verify the efficacy of the proposed method.     

Design Optimization of a Bionic Fish with Multi-Joint Fin Rays

This paper aims to design a novel bionic fish propelled by oscillating paired pectoral fins. Flapping motion deformation of the nature sample, the cow-nosed ray, is realized with simple mechanical structure through optimization. Locomotion analysis of the nature sample under linear cruise swimming conditions is carried out. Simplified mathematical models of the pectoral fin are obtained to be the design foundation of the bionic fin rays and the bionic fish. The number of fin rays is decided according to the passing kinematic wave shape and number. Distance and structure parameters are optimized, and determined by the minimum area error method. A novel two-stage slide–rocker mechanism is designed to fulfill the driving requirements with only one servo motor. System design of a new bionic fish robot is presented, including the mechanical design and the control method. Main bionic characteristics extracted from the cow-nosed ray are fulfilled by the prototype and verified by experiments.     

Backward swimming gaits for a carangiform robotic fish

This paper focuses on the gaits planning method of the backward swimming for unsymmetrical structure bio-inspired robotic fish. Based on the differences between the anguilliform mode and carangiform mode swimming, a method for searching gaits of backward swimming was proposed to plan the motion of the developed carangiform robotic fish. The body envelope of European eel’s backward swimming was mimicked according to the freely swimming model, which was proposed to analyze the propulsion produced by the undulation of the multi-link tail. Finally, simulations and experiments were conducted to demonstrate the gaits searching method for the bio-inspired carangiform robotic fish.     

仿鲹科机器鱼的倒退游动控制

给出了一种新型的仿鲹科机器鱼倒退游动控制方法. 在已有多关节仿鲹科机器鱼的基础上, 仿照欧洲鳗鱼的倒退运动机理, 修正机器鱼尾部关节的摆动规律, 进而实现倒游运动. 给出鲹科机器鱼游动的定性分析, 用于分析仿鲹科机器鱼推进机理和倒退游动的方法. 组合其他运动, 实现倒退游动、倒游中转弯等运动. 通过实验, 给出了机器鱼摆动频率和倒退运动速度之间的关系, 验证了本文所提方法的有效性.     

Electrostatically Actuated Robotic Fish: Design and Control for High-Mobility Open-Loop Swimming

This paper presents a project that aims at fabricating a biologically inspired robotic fish. The robotic fish is designed to be capable of propelling itself through oscillations of a flexible caudal fin, like a real underwater fish. In this paper, we describe the design features that underlie the operation of the robotic fish. These features include a unique actuator referred to as electrostatic film motor and a light and flexible power transmission system. The electrostatic film motor is made of two pieces of flexible printed circuit film and can be utilized as a new-type artificial muscle. The power transmission system permits reciprocating power to be converted to periodic oscillations and distributed to the caudal fin. Based on several design considerations inspired by biological concepts, we propose several open-loop swimming control strategies for the constructed robotic fish to accomplish fish-like motion (i.e., cruising, turning, and diving). Experiments of Seidengyo I, the first prototype of our electrostatic fish family, are carried out to confirm the validity of the original design and control. We further design Seidengyo II to improve on Seidengyo I and show the results of the experiments.     

仿生机器鱼俯仰与深度控制方法

提出一种基于重心改变法的仿生机器鱼俯仰姿态与深度控制方法, 用于实现机器鱼水中的浮潜运动. 该方法利用一种可调整位置的配重块结构, 改变机器鱼的重心位置, 进而实现机器鱼俯仰姿态的调节. 在对机器鱼内部配重块位置和机器鱼俯仰角的关系进行分析的基础上, 对一定速度下机器鱼的深度与俯仰角的关系进行建模, 提出由于尾部形变引起的俯仰姿态变化的补偿方法. 文中给出机器鱼原形样机的相关实验, 分析验证配重块位置变化和机器鱼重心及其姿态的调整, 深度控制等在多种情况下的结果.     

NiTi形状记忆合金驱动的仿生鱼鳍的研究

为了提高仿鱼型推进器在水中运动的灵活性，选择了典型的依靠腹部绸带状鱼鳍波动运动产生推进力的黑色魔鬼刀鱼进行研究，对此绸带状鱼鳍的形态和运动机理进行了分析，同时对鱼鳍的结构进行简化．基于绸带状鱼鳍的这种简化模型设计了形状记忆合金驱动的仿生鱼鳍．介绍了鱼鳍的机械结构和相应的控制电路．重点推导了仿生鱼鳍波状运动时理论上能到达的推进速度和产生的推进力；并采用数值仿真给出了波动推进时仿生鱼鳍表面的压力分布以及推进力随时间的周期变化规律．将数值仿真结论和先前的实验结果进行了比较，验证了数值仿真的合理性和正确性．通过上述分析，说明基于形状记忆合金驱动的仿生鱼鳍的研究是很有意义而且可行的．     

仿生机器鱼胸/尾鳍协同推进闭环深度控制

为改善机器鱼定深控制过程中的动态性能与稳态性能,根据深度误差的大小将定深控制过程分解为趋近阶段与巡游阶段,给出了一种基于中枢模式发生器（central pattern generator,CPG）与模糊控制相结合的闭环运动控制方法．为此,首先建立了以压力传感器信号为反馈输入,通过模糊控制器调节控制参数的CPG运动控制模型．在此基础上,针对误差较大的趋近阶段,采用胸/尾鳍协同方式,通过趋近模糊控制器改变摇翼关节的偏置量与幅值来使机器鱼快速到达期望深度;针对误差较小的巡游阶段,采用改变攻角方式,通过巡游模糊控制器改变胸鳍攻角来使机器鱼保持在期望深度．两阶段之间通过胸鳍CPG的启停实现切换．模糊控制器设计时利用了基于最小二乘法对实验数据拟合而得出的俯仰角变化率与控制参数的近似关系,提高了机器鱼趋向期望深度的速度并减小了在期望深度巡游时的稳态误差．仿真与实验结果验证了所提控制方法的有效性．     

基于序列图像处理法的机器鱼转向机动性能研究

基于序列图像处理法，对机器鱼的转向性能进行了初步研究．利用高速摄像机记录机器鱼运动过程， 对游动序列图像进行处理，提取机器鱼体干曲线，获取机器鱼转向运动中角度、角速度、角加速度的动态特性．根 据实验结果，给出了机器鱼C 形转向运动的3 个阶段的运动特征，并对理论值和实验测定值之间的差异进行分析． 同时，对静止和运动两种C 形转向运动进行比较，分析了影响C 形转向效果的因素：初始动能以及保持阶段角度大 小，在此基础上，给出了提高机器鱼转向性能的方法．     

基于干扰观测器的机械臂广义模型预测轨迹跟踪控制

为实现对多自由度机械臂关节运动精确轨迹跟踪,提出一种基于非线性干扰观测器的广义模型预测轨迹跟踪控制方法。针对机械臂轨迹跟踪运动学子系统,采用广义预测控制（Generalized Predictive Control,GPC）方法设计期望的虚拟关节角速度。对于机械臂轨迹跟踪动力学子系统,考虑机械臂的参数不确定性和未知外界扰动,利用GPC方法设计关节力矩控制输入,基于非线性干扰观测器方法实时估计和补偿系统模型中的不确定性。在李雅普诺夫稳定性理论框架下证明了机械臂关节角位置和角速度的跟踪误差最终收敛于零的小邻域。数值仿真验证了所提出控制方法的有效性和优越性。     

HOJO-brain for motion control of robots and biological systems

The purpose of this research was to propose and develop a control method in the robotic and biomedical fields which is configured by a robotic/biological simulator, an analytical control frame which has phase sequences, sensory feedback, and an artificial central pattern generator (CPG) which is constructed by a recurrent neural network (RNN) and a genetic algorithm (GA). We call such a controller a “HOJO-brain”, which means a supplementary brain for motion control. We applied this method in the robotic and biomedical fields. In the robotic field, the HOJO-brain was applied to a 5-DOF legged-locomotion robot and a 32-DOF humanoid simulation model consisting of antagonistic muscles. In the biomedical field, it was applied to animals as the FES (functional electrical stimulation) controller. This FES control system with a HOJO-brain has the potential to give more effective and emergent motion control to severely physically handicapped people such as quadraplegics. With computer simulations and simple experiments using animals, we abtained performance indices which confirmed the fine adaptability and emergence for motion control. This work was presented, in part, at the Second International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1997     

两类仿鲹科机器鱼倒游运动控制方法的对比研究

给出并比较了两类分别采用鱼体波动方程和中枢模式发生器（Central pattern generator,CPG）控制仿鲹科机器鱼倒游运动的方法.前者主要通过修改鱼体波动方程、颠倒机器鱼各个关节的控制规律来实现 鱼体倒游;后者则基于CPG模型,产生各个关节的节律控制信号.基于CPG的倒游方法可进一步细分为两种:1） 相位颠倒的CPG控制方法,即通过逆转CPG控制机器鱼直游的相位关系;2） 相位-幅值颠倒的CPG控制方法,即通过逆转鱼体波的传播方向和摆动幅值来实现机器鱼倒游.文中针对这两大类、三种机器鱼倒游运动控制方法 进行了分析、仿真和实验.实验结果表明:在相同参数配置下,采用相位颠倒的CPG控制方法产生的倒游速度最大,但游动对水的扰动也最大;而采用鱼体波倒游和相位-幅值颠倒的CPG控制方法时,两者产生的最大倒游速度相差不大,扰动较小.此外,采用鱼体波倒游方法在频率切换时会有抖动现象,需要设计专门的过渡函数来消除;而采用CPG模型的方法 则可以实现平滑过渡.上述结果对提高水下游动机器人的机动性能具有重要的指导意义.     

空间机器人抓捕目标后基于任务相容性的消旋策略

针对双臂空间机器人抓捕自旋目标后的镇定操作,在考虑机器人系统输入约束的条件下,提出了一种基于任务相容性的消旋规划与控制方法。首先,给出空间机器人抓捕目标后的组合系统的动力学模型,作为规划与控制的基础。然后,根据动力学可操作度和任务相容性设计了目标的快速消旋策略,其期望加速度的方向和大小分别取作速度的反方向和机器人系统输入约束允许的最大值。最后,基于所推导的运动学和动力学模型,通过对目标和机械臂末端分别建立柔顺度等式,提出了一种跟踪期望运动轨迹同时对末端接触力进行调节的柔顺控制方法。通过双臂7自由度空间机器人消除目标自旋运动的仿真结果,验证了所提方法的有效性。     

Autonomous Path Planning and Experiment Study of Free-floating Space Robot for Target Capturing

Space robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the capturing technology, becomes research hot in recent years. In this paper, the authors propose an autonomous path planning method for target capturing. The task is described in Cartesian space and it can drive the manipulator to approach the target along the closest path. Firstly, the target feature is extracted based on the measured information via the hand-eye camera, and the target pose (position and orientation) and velocities (linear velocity and angular velocity) are estimated using Kalman filtering technology. Then, a numerically feasible approach is presented to plan the manipulator motion and avoid the dynamic singularities, which are transformed into real-time kinematic singularities avoiding problem. Thirdly, the potential disturbance on the base due to the manipulator’s motion is estimated, and the joint rates are autonomously adjusted to reduce the disturbance if it is beyond the allowed bound. At last, a ground experiment system is set up based on the concept of dynamic emulation and kinematic equivalence. With the experiment system, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm.     

A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

Taking advantage of their inherent dexterity, robotic arms are competent in completing many tasks efficiently. As a result of the modeling complexity and kinematic uncertainty of robotic arms, model-free control paradigm has been proposed and investigated extensively. However, robust model-free control of robotic arms in the presence of noise interference remains a problem worth studying. In this paper, we first propose a new kind of zeroing neural network (ZNN), i.e., integration-enhanced noise-tolerant ZNN (IENT-ZNN) with integration-enhanced noise-tolerant capability. Then, a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms, which improves the performance of robotic arms with the disturbance of noise, without knowing the structural parameters of the robotic arms. The finite-time convergence and robustness of the proposed control scheme are proven by theoretical analysis. Finally, simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.