基于CPG的并联腿四足机器人步态控制

并联腿结构的四足机器人具有承载能力强、刚度大、运动精度高的优点,但控制复杂。为更好地控制,提出了一种串联结构等效方法对并联腿进行了分析,结合中枢模式发生器（CPG）对等效的髋、膝关节进行控制,从而实现四足机器人不同步态,并利用ADAMS与MATLAB/SIMULINK软件搭建了四足机器人的虚拟样机与控制系统。仿真实验结果表明,串联等效分析方法能够应用于并联腿结构,CPG可实现四足机器人的Walk与Trot步态,验证了该方法的可行性与有效性。     

仿生六足机器人步态设计与运动仿真

仿生六足机器人稳定性好、灵活度高在众多领域得到了使用。为实现对六足机器人的运动控制和性能分析,通过构建机器人D-H连杆坐标系结合机械结构参数,确定了运动学正解、逆解表达式;设计可修改参数的机器人行走参考步态,引入了控制机体保持水平的姿态控制和适应不平整地形的腿着陆控制。以MATLAB的Simulink作为仿真环境,构建机器人模型,完成运动仿真,并对测量到的运动数据和腿部关节输出力矩进行分析。其结果表明,机器人能够跟随所设计步态生成的轨迹连续稳定行走,使用基于模型设计的方法,验证了所提算法的正确性和可行性,最后得到了腿部各关节力矩分布,为后续六足机器人设计与运动控制提供参考。     

四足机器人节律柔顺行走控制

针对节律运动突变碰撞力大和柔顺性低的问题,改进基于Hopf振荡器的中枢模式发生器模型,提出一种节律柔顺行走控制方法。分析Hopf振荡器输出信号与关节运动之间的关系,整合膝关节变量,改变神经元之间的作用关系,实现对称步态和非对称步态行走;分析节律运动碰撞力突变对四足机器人行走产生的负面影响,提出基于碰撞力大小和四足机器人身体姿态的柔顺性评估方法;通过连续调整碰撞阶段大腿的摆动幅度,增大摆动周期,减小碰撞阶段的关节运动速度,形成机器人本体与地面之间的缓冲,实现节律柔顺行走。四足机器人慢走步态和对角小跑步态仿真实验验证了该控制方法的有效性。     

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...     

基于CPG的沙漠蜘蛛机器人多模式运动控制方法

模仿具有多种运动模式的沙漠蜘蛛,设计了本体为双层六杆5R闭链机构的仿蜘蛛机器人,其中16个主动关节由直流伺服电机控制．提出了基于Hopf振荡器的中枢模式发生器（CPG）运动控制模型,用于实现仿蜘蛛机器人的翻滚、爬行、侧滚等多种运动模式以及步态切换．利用Matlab和ADAMS对仿蜘蛛机器人的多模式运动进行动力学仿真,结果表明机器人可实现连续平稳的翻滚、爬行、侧滚运动,验证了CPG仿生控制方法应用于闭链机器人多模式运动的可行性．     

基于Hopf振荡器实现的蛇形机器人的步态控制

针对生物蛇不同步态的运动特点,提出了一种基于Hopf振荡器实现的蛇形机器人的中枢模式发生器(CPG)运动控制方法.首先,利用具有非线性极限环特性的耦合的Hopf振荡器构建出能够实现蜿蜒运动和侧向蜿蜒运动两种步态的链式网络模型.然后,根据动力学仿真软件建立机器人的虚拟样机,利用模型中振荡器的输出作为蛇形机器人分布式多冗余度关节的控制信号来驱动前进,成功实现了以上两种运动方式,并讨论了CPG的模型参数与机器人前进速度的关系.最后,在实物样机上的实验进一步验证了所提出的方法在实现蛇形机器人多种步态控制方面的有效性.     

基于GA优化双足机器人步态控制的CPG模型研究

由于传统人工规划产生步态是比较僵硬,缓慢的,缺乏灵活的自组织能力,与真正生物步态存在很大差异;而生物能很好利用中枢模式发生器的自激行为产生有节律的协调运动从而适应多种复杂环境,但普通CPG控制策略又会使关节间出现抖动,影响步态的控制效果;文中提出了以生物中枢模式发生器模型为核心建立双足机器人控制系统,并对CPG的参数进行遗传算法的高效优化,提高了系统性能,消除了关节的抖动;通过MATLAB仿真验证基于GA参数优化的CPG控制机理的双足机器人节律运动控制方法是有效的,并得到了很好的控制效果。     

有脊椎四足机器人递阶CPG步态规划与速度分析

针对动物脊椎协调运动分析以及不同速度下的步态参数分析困难等问题,为了更好的控制输入速度,产生相适应的步态模式,设计三层递阶式网络步态规范方法。分析trot步态下速度与角频率ω的关系;分析bound步态下速度与髋关节幅值A_h之间的关系;通过Webots仿真分别验证了trot和bound步态下各自速度与步态参数之间映射关系的合理性。通过误差分析,角频率误差在0.25 rad/s左右,髋关节幅值误差在0.02 rad左右;在bound步态下,通过加入脊椎,对比仿真分析得出,脊椎运动可加快机器人速度,同时改变肢体和脊椎幅值相比于只改变肢体幅值更合理。     

控制六足仿生机器人三角步态的研究

基于仿生学原理,在分析六足昆虫运动机理的基础上,对六足仿生机器人的三角步态运动原理进行了分析.论文涉及六腿机器人步态研究的一些基本参数的描述,讨论了用相对运动的原理研究步态的方法,结合慧鱼机器人组合包中的构件拼出六足仿生机器人.该机器人模型结构简单,设计独特,能前进和后退,且能避开小型障碍物.基于三角步态运动原理对其进行了反复实验,实验结果表明六足仿生机器人具有较好的机动性和稳定性.     

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.     

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.     

A gait study for a one-leg-disabled hexapod robot

—As a remarkably strong point of a hexapod walking robot, it is considered that even if one of the six legs is disabled, static walking may be maintained by the remaining five legs. However, to maintain the static stability at maximum, a gait study for five-legged walking is a necessary factor. Hence, this paper describes a method of gait study for such a situation. Since it is very difficult to find a suitable gait by use of an analytical method without any model, such as a model based on insects' walking, we employed a programming method with the help of recent powerful computers. Some devices are applied to reduce the number of computations. As a result, we have obtained two kinds of gaits which can maintain the gait stability margin at a high level for a duty factor in the range of 0.6β < 1.     

Planar legged walking of a passive-spine hexapod robot

This paper proposes a new legged walking method for a novel passive-spine hexapod robot. This robot consists of several body segments connected by passive body joints. Each of the body segments carries two 1-DoF (degree of freedom) actuated legs. The robot is capable of achieving planar legged walking by rapidly abducting and adducting its legs. To model the mobility of a robot based on this simple design, the candidate configurations from all possible configurations are first selected in a mobility analysis of the robot based on the screw theory. All the feasible sequences of these candidate configurations are then searched to form planar locomotion gaits. Next, locomotive performance of the gaits is analyzed. Finally, the proposed locomotion design and gait planning methods are verified through simulations and experiments.     

Optimal design and motion control of biomimetic robotic fish

This paper is concerned with the design, optimization, and motion control of a radiocontrolled, multi-link, free-swimming biomimetic robotic fish based on an optimized kinematic and dynamic model of fish swimming. The performance of the robotic fish is determined by both the fish＇s morphological characteristics and kinematic parameters. By applying ichthyologic theories of propulsion, a design framework that takes into consideration both mechatronic constraints in physical realization and feasibility of control methods is presented, under which a multiple linked robotic fish that integrates both the carangiform and anguilliform swimming modes can be easily developed. Taking account of both theoretic hydrodynamic issues and practical problems in engineering realization, the optimal link-lengthratios are numerically calculated by an improved constrained cyclic variable method, which are successfully applied to a series of real robotic fishes. The rhythmic movements of swimming are driven by a central pattern generator （CPG） based on nonlinear oscillations, and up-and-down motion by regulating the rotating angle of pectoral fins. The experimental results verify that the presented scheme and method are effective in design and implementation.     

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.     

基于离散化的六足机器人自由步态规划

为精细模仿生物步态,充分发挥六足机器人运动潜能,本文在离散化机器人足端轨迹的基础上,融合中枢模式发生器(central pattern generator,CPG)模型与反射模型的核心思想,建立了离散化步态模型,结合稳定性分析,构建了机器人稳定的位置状态空间,将复杂的步态规划问题转化为稳定的位置状态空间中位置状态间的排序问题,在此基础上,提出了一种新的自由步态生成算法,并基于平均稳定裕量对该算法进行了优化.样机步态实验结果表明,自由步态生成算法与自由步态优化算法均可生成在一定程度上符合生物运动特点的稳定步态,实现机器人运动过程中速度的动态调整,跨越宽度为步距的障碍,且基于平均稳定裕量的自由步态优化算法生成步态的稳定性要远大于自由步态生成算法.     

基于模型预测—中枢模式发生器的六足机器人轨迹跟踪控制

为了模仿动物卓越的运动能力和环境适应能力,提出了六足仿生机器人的轨迹跟踪控制方法。首先建立了机器人的运动学模型,接着通过转向参数将机器人的速度和角速度与中枢模式发生器（CPG）参数结合起来,设计了转换函数。然后通过转换函数将模型预测控制器和CPG网络结合起来,提出了基于CPG的模型预测控制器（MPC-CPG）,并证明了其稳定性。最后对机器人跟踪圆周轨迹和直线轨迹进行了仿真和实验。实验表明,在有初始误差的条件下,机器人在MPC-CPG控制器的作用下能够快速地消除位置误差和航向角误差,跟踪上参考轨迹。轨迹跟踪的位置误差始终保持在-0.1～0.1 m,航向角误差保持在-27?～20?。在MPC-CPG控制器的作用下,机器人不仅具有较高的轨迹跟踪精度,同时还表现出良好的运动平滑性和协调性,进一步验证了所提出的MPC-CPG控制器的有效性。     

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.