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.     

一种面向机器鱼的高精度位姿控制算法设计与实现

首先应用一种简单的线性 CPG（中枢模式发生器）模型,实现了机器鱼游动模态的连续变化．随后通过实验分析得到 CPG 控制器控制参数与机器鱼速度和转弯角速度的转换层函数．进一步提出一种改进的比例导引位姿控制算法,以一种新的方式定义机器鱼的位姿误差,再将机器鱼的角度误差作为偏置项加入位置误差的比例控制律中．最后通过实验验证了算法的可行性与有效性．     

胸鳍推进型机器鱼的CPG 控制及实现

结合仿生游动机理,针对胸鳍推进型机器鱼提出了一种基于中枢模式发生器（CPG）的运动控制方法．该模型采用一类振荡频率和幅值可以独立控制的非线性微分方程作为其神经元振荡器模型,通过最近相邻耦合的方式,对n 个这样的神经元振荡器进行耦合,构建了仿生机器鱼的CPG 网络模型．证明了此模型单个神经元振荡器的极限环的存在性、唯一性及稳定性．在此基础上,通过对胸鳍推进的运动学分析,导出机器人直游、倒游、胸鳍—尾鳍协调运动等多种模式的运动控制方法．仿真及实验结果验证了此中枢模式发生器模型的可行性与所提控制方法的有效性．     

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.     

Mechanical design and motion control of a biomimetic robotic dolphin

This paper addresses the design, construction and control issues of a novel biomimetic robotic dolphin equipped with mechanical flippers, based on an engineered propulsive model. The robotic dolphin is modeled as a three-segment organism composed of a rigid anterior body, a flexible rear body and an oscillating fluke. The dorsoventral movement of the tail produces the thrust and bending of the anterior body in the horizontal plane enables turning maneuvers. A dual-microcontroller structure is adopted to drive the oscillating multi-link rear body and the mechanical flippers. Experimental results primarily confirm the effectiveness of the dolphin-like movement in propulsion and maneuvering.     

机器海豚多模态游动CPG控制

受自然界海豚超凡的水中游动技能启发,机器海豚在军事和民用上具有潜在的广泛应用前景,因此受到研究人员的极大关注. 然而,要实现机器海豚在水中自如地机动游动,必须为机器海豚设计一个具有丰富游动技能的多模态控制器. 为此,通过振荡器建模与分析、中枢模式发生器（Central pattern generation,CPG）与机器海豚关节配对、CPG单元间耦合等环节建立了机器海豚的链式弱耦合CPG运动控制模型,提出一种基于CPG激发产生多模态振荡波形控制机器海豚运动的方法. 详细阐述了机器海豚样机研制、控制器设计、运动控制实现与实验测试等内容. 向前直游、转弯、浮潜等游动实验结果验证了所提出的机器海豚CPG运动控制方法的有效性和实用性.     

基于CPG的六足机器人运动步态控制方法

中枢模式发生器(CPG)在六足机器人的运动步态控制中起着至关重要的作用。为了研究六足机器人的运动控制方法,首先基于仿生学原理设计了六足机器人的机械结构,并在虚拟样机软件ADAMS中搭建其三维模型;其次选择Hopf振荡器作为CPG单元,并改进了振荡器模型;然后设计了六足机器人的CPG网络拓扑结构,包含单腿关节映射函数方案和腿间CPG环形耦合网络方案,并对其进行了改进;最后通过ADAMS和MATLAB联合仿真实验,验证了所设计六足机器人的运动稳定性和CPG控制方案的可行性与有效性。仿真结果表明,该方法能够满足六足机器人不同运动步态的控制需求,对六足机器人的运动控制具有一定的实际应用价值。     

基于CPG的仿生环形长鳍波动推进器运动控制

为了克服一般仿生水下机器人稳定性与机动性的不足,提出一种仿生环形长鳍波动推进器及其控制方法．根据环形长鳍波动推进器的结构特征和推进机理,提出了基于中枢模式发生器（CPG）的运动控制方法．该方法通过相邻耦合的方式,对波动推进器中20个频率和幅值可独立控制的神经元振荡器进行了建模,构建了一种用于该推进器的CPG网络模型．仿真分析了对称波形、非对称波形和环形波形推进控制方式下控制模型中的各振荡子输出信号,以及各参数对输出信号的影响,并试验研究了波形参数对样机游动速度和转弯速度的影响．试验结果显示样机具有一定的稳定性与机动性,直线游动速度和原地转弯速度随波动频率和波动幅值的增大而增大,最大直线游动速度可达109mm/s,最大原地转弯速度可达93°/s．仿真及试验结果证明了此CPG控制模型的可行性和有效性．     

基于Fuzzy–CPG的双足机器人适应性行走控制

为提高双足机器人的环境适应性,本文提出了一种基于模糊控制与中枢模式发生器(CPG)的混合控制策略,称之为Fuzzy–CPG算法.高层控制中枢串联模糊控制系统,将环境反馈信息映射为行走步态信息和CPG幅值参数.低层控制中枢CPG根据高层输出命令产生节律性信号,作为机器人的关节控制信号.通过机器人运动,获取环境信息并反馈给高层控制中枢,产生下一步的运动命令.在坡度和凹凸程度可变的仿真环境中进行混合控制策略的实验验证,结果表明,本文提出的Fuzzy–CPG控制方法可以使机器人根据环境的变化产生适应的行走步态,提高了双足机器人的环境适应性行走能力.     

节律性步态运动中CPG对肌肉的控制模式的仿真研究

以神经振荡器理论和Dingguo Zhang等人研究的CPG模型为基础,结合了神经生物学和生物动力学的观点,并根据人体腿部的肌肉结构修正了Dingguo Zhang等提出的中枢模式发生器(CPG)的数学模型.修正后的CPG模型突破了原来仅反映单腿的节律性运动的局限性,能够更好地描述步态运动中双腿的节律性与协调性,使得修正后的CPG模型与实际情况更为一致.依据本文所提出的修正模型所做的数值模拟结果表明,我们所得到的CPG的输出模式能够很好的表现出人体节律性步态运动中神经系统的调节作用.     

基于UMAC的六足机器人控制系统设计

六足机器人随着任务的复杂程度不断提高,自由度也不断增多,使其控制结构也越来越复杂,给工程实现带来很大的困难.本文以中枢模式发生器(CPG)原理为基础,IPC+UMAC多轴运动控制器为核心,采用分级分布式控制结构设计六足机器人控制系统.控制系统包括6个CPG单元,每个CPG单元的输出信号控制机器人单腿的三个关节.通过CP...     

An adaptive locomotion controller for a hexapod robot: CPG,kinematics and force feedback

Insects can perform versatile locomotion behaviors such as multiple gaits, adapting to different terrains, fast escaping, etc. However, most of the existing bio-inspired legged robots do not possess such walking ability, especially when they walk on irregular terrains. To tackle this challenge, a central pattern generator （CPG）-based locomotion control methodology is proposed, integrated with a contact force feedback function. In this approach, multiple gaits are produced by the CFG module. After passing through a post-processing circuit and a delay-line, the control signal is fed into six trajectory generators to generate predefined feet trajectories for the six legs. Then, force feedback is employed to adjust these trajectories so as to adapt the robot to rough terrains. Finally the regulated trajectories are sent to inverse kinematics modules such that the position control instructions are generated to control the actuators. In both simulations and real robot experiments, we consistently show that the robot can perform sophisticated walking patterns. What is more, the robot can use the force feedback mechanism to deal with the irregularity in rough terrain. With this mechanism, the stability and adaptability of the robot are enhanced. In conclusion, the CPG-base control is an effective approach for legged robots and the force feedback approach is able to improve walking ability of the robots, especially when they walk on irregular terrains.     

Optimal and Robust Control of Multi DOF Robotic Manipulator: Design and Hardware Realization

Robots have become an integral part of industrial automation. Their ultimate role and contribution in this sector is essentially a function of the associated control strategy to ensure precision, repeatability, and reliability, particularly in an environment polluted with disturbances and uncertainties. This research aims to present a design of the modern control strategies for a 6 degree of freedom robotic manipulator. Based on derived kinematic and dynamic models of the robot, optimal and robust control strategies are simulated and practically realized on a custom developed pseudo-industrial framework named as AUTonomous Articulated Robotic Educational Platform. Results of the experimental trials in terms of trajectory tracking demonstrate efficiency and usefulness of the presented control approaches.     

Walking Robots and the Central and Peripheral Control of Locomotion in Insects

This paper outlines aspects of locomotor control in insects that may serve as the basis for the design of controllers for autonomous hexapod robots. Control of insect walking can be considered hierarchical and modular. The brain determines onset, direction, and speed of walking. Coordination is done locally in the ganglia that control leg movements. Typically, networks of neurons capable of generating alternating contractions of antagonistic muscles (termed central pattern generators, or CPGs) control the stepping movements of individual legs. The legs are coordinated by interactions between the CPGs and sensory feedback from the moving legs. This peripheral feedback provides information about leg load, position, velocity, and acceleration, as well as information about joint angles and foot contact. In addition, both the central pattern generators and the sensory information that feeds them may be modulated or adjusted according to circumstances. Consequently, locomotion in insects is extraordinarily robust and adaptable.     

Adaptive motion control law of a robotic wheelchair

In the present work, a dynamic model of a robotic wheelchair is developed considering a lateral deviation of the center of mass. The Lyapunov and input/output stability theories are used to design a novel tracking and positioning adaptive control for the robotic wheelchair. Properties of the dynamic model with respect to its matrices and parameters are shown. A filter is used to obtain a closed loop equation that allows designing the adaptive control law. Then, a projection algorithm is used to improve the adaptive control in the sense of avoiding parameter drift. Experimental results show good performance of the adaptive control.     

基于运动控制卡的控制系统的设计与实现

本文介绍了一个基于多轴运动控制卡的运动控制系统。该系统以工控计算机、通用操作系统、PCI-8134多轴运动控制卡及其功能库函数为平台,采用VC++开发的人机界面,实现了三轴(X,Y,Z轴)独立运动、各个轴的连续直线运动以及梯形加减速运动等功能。     

Gaits-transferable CPG controller for a snake-like robot

With slim and legless body, particular ball articulation, and rhythmic locomotion, a nature snake adapted itself to many terrains under the control of a neuron system. Based on analyzing the locomotion mechanism, the main functional features of the motor system in snakes are specified in detail. Furthermore, a bidirectional cyclic inhibitory （BCl） CPG model is applied for the first time to imitate the pattern generation for the locomotion control of the snake-like robot, and its characteristics are discussed, particularly for the generation of three kinds of rhythmic locomotion. Moreover, we introduce the neuron network organized by the BCI-CPGs connected in line with unilateral excitation to switch automatically locomotion pattern of a snake-like robot under different commands from the higher level control neuron and present a necessary condition for the CPG neuron network to sustain a rhythmic output. The validity for the generation of different kinds of rhythmic locomotion modes by the CPG network are verified by the dynamic simulations and experiments. This research provided a new method to model the generation mechanism of the rhythmic pattern of the snake.     

Models,feedback control,and open problems of 3D bipedal robotic walking

The fields of control and robotics are working toward the development of bipedal robots that can realize walking motions with the stability and agility of a human being. Dynamic models for bipeds are hybrid in nature. They contain both continuous and discrete elements, with switching events that are governed by a combination of unilateral constraints and impulse-like forces that occur at foot touchdown. Control laws for these machines must be hybrid as well. The goals of this paper are fourfold: highlight certain properties of the models which greatly influence the control law design; overview the literature; present two control design approaches in depth; and indicate some of the many open problems.     

Indirect disturbance compensation control of a planar parallel (2-PRP and 1-PPR) robotic manipulator

This study addresses the dynamic modelling and indirect disturbance compensation control of planar parallel robotic motion platform with three degrees of freedom (3-DOF) in the presence of parameter uncertainties and external disturbances. The proposed planar parallel motion platform is a singularity free manipulator and has three manipulator legs located on the same plane linked with a moving platform. Of the three aforementioned manipulator legs, two legs have a prismatic–revolute–prismatic (PRP) joint configuration each with only one prismatic joint deliberated to be active, and the other leg consists of prismatic–revolute–prismatic (PPR) joint configuration with one active prismatic joint. The closed form kinematic solution (both forward and reverse kinematics) for the platform has been obtained in completion. In addition, the dynamic model for the platform has been communicated using the energy based Euler–Lagrangian formulation method. The proposed controller is based on a computer torque control with disturbance compensation integrated with it. Disturbance vectors comprising disturbances due to parameter variations, payload variations, frictional effects and other additional effects have been estimated using an extended Kalman filter (EKF). The EKF proposed for this specific platform uses only position and orientation measurements for estimation and noise mitigation. Simulations with a characteristic trajectory are presented and the results have been paralleled with traditional controllers such as the proportional integral derivative (PID) controller and computed torque controller (CTC). The results demonstrate satisfactory tracking performance for the proposed controller in the presence of parameter uncertainties and external disturbances.