基于遗传算法的蛇形机器人CPG模型参数优化

针对蛇形机器人采用的循环抑制CPG模型,为解决CPG控制模型中参数整定效率低、不稳定的问题,阐述基于CPG模型的蛇形搜救机器人控制系统总体方案的设计,提出一种基于遗传算法的CPG控制模型参数优化方法,实现链式CPG网络的节律输出。仿真实现蛇形搜救机器人各关节控制信号的有效输出,仿真结果表明,该方法具有高效、准确、稳定等优点,可有效应用于蛇形搜救机器人的步态控制。     

基于PSO蛇形机器人CPG控制模型参数的优化

针对蛇形机器人链式CPG(central pattern generator)复杂模型,提出了采用粒子群算法(particle swarm optimization)优化CPG控制模型参数,用来解决CPG参数整定效率低、效果不理想的问题,然后结合Webots机器人仿真软件,实现了PSO算法优化蛇形机器人CPG控制模型参数。最后利用Webots仿真软件,通过实验仿真与遗传算法的结果相对比,证实了PSO算法的优越性,为蛇形机器人的运动步态转换提供好的基础。     

融合机械元的蛇形机器人循环抑制中枢模式发生器控制方法

针对蛇形机器人中枢模式发生器(CPG)控制中控制信号以及传感信息缺少选择依据的问题,提出了一种融合了机械元的循环抑制CPG控制方法.首先,将蛇形机器人本体动力学方程改造为机械元引入循环抑制CPG模型.其次,提出了改进的Matsuoka神经元,从而使得神经元与机械元具有一致的表达形式.再次,分析了融入机械元的循环抑制CPG模型中的参数关系,并给出了控制信号和传感信息与CPG状态量关系的表达式.最后,利用仿真对所提出的方法进行了验证,并对产生结果进行了分析.该方法中蛇形机器人的控制信号与传感信息都具有明确的定义,且由于用机械元的物理结构代替了神经元的计算,降低了CPG的计算量.     

基于循环抑制CPG 模型控制的蛇形机器人三维运动

具有三维运动能力和独特的节律运动方式，使生物蛇能在复杂的地形环境中生存. 大多数动物节律运动是由中央模式发生器(Central pattern generator, CPG) 控制的. 以此为理论依据, 首次以循环抑制建模机理构建蛇形机器人组合关节运动控制的CPG 模型. 证明该模型是节律输出型CPG 中微分方程维数最少的. 采用单向激励方式连接该类CPG 构建蛇形机器人三维运动神经网络控制体系，给出该CPG 网络产生振荡输出的必要条件. 应用蛇形机器人动力学模型仿真得到控制三维运动的CPG 神经网络参数，利用该CPG 网络的输出使\勘查者"成功实现三维运动. 该结果为建立未探明的生物蛇神经网络模型提供了一种全新的方法.     

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.     

基于双层级CPG的3维蛇形机器人运动控制方法

为实现3维蛇形机器人多模式运动控制,提出了一种基于双层级中枢模式发生器(CPG)的运动控制方法.该双层级CPG网络包含节律层和模式层,节律层的CPG神经元用于控制3维蛇形机器人的俯仰关节组和偏转关节组的相位关系,模式层的CPG神经元用于控制3维蛇形机器人关节组内各个关节的相位差及关节轨迹.首先,利用Kuramoto振荡器对CPG神经元进行建模,并确定CPG网络的层级结构和耦合拓扑;然后,基于蛇形约束曲线计算3维蛇形机器人侧滚运动、侧移运动、滑行运动及转向运动4种典型运动步态的控制参数;最后,通过联合仿真和实验验证该双层级CPG网络的控制性能.由实验结果可知,3维蛇形机器人的侧滚运动、侧移运动、滑行运动以及转向运动的实际速度分别能够达到3.9 cm/s、9.0 cm/s、2.1 cm/s和10.8°/s.因此,该方法能够有效地、灵活地控制3维蛇形机器人的多模式运动.     

基于Webots的蛇形机器人翻滚运动仿真及实现

针对蛇形机器人的侧向翻滚运动,给出一种建立正交关节蛇形机器人三维空间运动模型的方法,提出了一种更为简单的实现蛇形机器人侧向翻滚运动的舵机输入函数.通过选择不同的控制参数,可以实现蛇形机器人"U"字形和"V"字形侧向翻滚运动.在Webots移动机器人仿真软件上进行正交关节蛇形机器人翻滚运动仿真,并在蛇形机器人本体上进行试验,验证了所提控制规律的有效性.     

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。     

蛇形机器人水下3D运动建模与仿真

由于蛇形机器人具有多关节、超冗余自由度的特点,以及水环境高度复杂非线性化,使得蛇形机器人的水下3维步态难以通过实验进行验证、分析及优化针对这些问题,根据蛇形机器人样机"探查者Ⅲ",搭建了水下运动的仿真分析系统.首先,分析了蛇形机器人水下运动时不同姿态下的水静力,计算了机器人受到的附加质量力和黏滞阻力的线性项和非线性项,并研究了流体力矩对水下运动的影响.然后,基于Morison方程建立了机器人与水交互的力学模型.最后,在仿真分析系统中对逐节下潜步态进行仿真,分析机器人的运动性能,并进行相应的实验.通过前进速度、下潜速度、运动趋势的对比表明:该力学模型能比较准确地模拟机器人与水环境的交互作用,仿真分析系统能用来验证和分析蛇形机器人的水下3维运动步态.     

基于改进蛇形曲线的蛇形机器人在流场中避障的轨迹跟踪控制律

针对蛇形机器人在流场中各关节之间的轨迹跟踪问题,研究一种基于改进蛇形曲线的蛇形机器人在流场中避障的轨迹跟踪控制律.首先,考虑流体环境可能施加在蛇形机器人系统上的外部干扰,采用浸入边界-格子Boltzmann方法(IB-LBM)在流场中建立障碍通道和蛇形机器人的流固耦合模型.然后,对蛇形机器人加入势函数,使其可以避开障碍;并采用改进的蛇形曲线方程使机器人尾部各关节跟踪头部的运动轨迹.最后,通过Matlab仿真和实验,研究不同流场密度、机器人尾部摆动频率以及流场雷诺数等参数对蛇形机器人轨迹跟踪的影响.理论分析和数值仿真表明,所设计的轨迹跟踪控制律不仅可以使蛇形机器人在遇到障碍时各关节跟踪前一关节的运动轨迹,而且还能使横向距离、纵向距离及方向角趋于稳定,达到有效避障的目的.此外,蛇形机器人在离开障碍通道后,各关节可以恢复蛇形曲线的运动形式,为蛇形机器人提供源源不断的前进动力.仿真和实验结果验证了轨迹跟踪控制律的有效性.     

A Simplified CPGs Network with Phase Oscillator Model for Locomotion Control of a Snake-like Robot

CPG (Central pattern generator) is a dynamical system of coupled nonlinear oscillators or neural networks inspired by a control mechanism in animal bodies. Without any rhythmic inputs, the CPG has the ability to produce oscillatory patterns. This paper presents a novel structure of a CPG network which can produce rhythmic motion that imitates movement of animals such as snake and lamprey. The focus is on the locomotion control of a snake-like robot, where phase oscillator has been adopted as the dynamical model to control the harmonic motion of the CPG network. There are two main points addressed in this paper: (1) simple network structure of unidirectional coupling oscillators, and (2) a single parameter to control the body shape and to control the forward and backward movement of the snake-like robot. The proposed CPG network is designed to have a simple structure with less complexity, less mathematical computation, fast convergence speed and exhibit limit cycle behavior. In addition, a new parameter, τ is introduced to control the smoothness of the CPG output as well as the speed of the snake-like robot. Simulation and experimental results show that the proposed CPG network can be used to control the serpentine locomotion of a snake-like robot.     

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.     

Adaptive creeping locomotion of a CPG-controlled snake-like robot to environment change

In this paper, we present a biomimetic approach which is based on Central Pattern Generator (CPG) to solve the difficulty in control of a snake-like robot with a large number of degrees of freedom. A new network with a feedback connection is proposed, which can generate uniform outputs without any additional adjustment. The relations between the CPG parameters and the characteristics of output are also investigated. A simulation platform is also established for the analysis of the CPG-based locomotion control of a snake-like robot. To figure out adaptive creeping locomotion of the robot to the environment with changed friction or the given slope, the relations of CPG parameters and locomotion efficiency by the proposed curvature adaptive principle have been discussed.     

Locomotion of snake-like robots using adaptive neural oscillators

This paper proposes a CPG-based control architecture using a frequency-adaptive oscillator for undulatory locomotion of snake-like robots. The control architecture consists of a network of neural oscillators that generates desired oscillatory output signals with specific phase lags. A key feature of the proposed architecture is a self-adaptation process that modulates the parameters of the CPG to adapt the motion of the robot to varying coefficients of body-ground friction. This process is based on the frequency-adaptation rule of the oscillator that is designed to learn the periodicity of sensory feedback signals. It has an important meaning of establishing a closed-loop CPG much more robust against environmental and/or system parameter changes. We verify the validity of the proposed locomotion control system employing a simulated snake-like robot moving over terrains with different friction coefficients with a constant velocity.     

新型蛇形机器人蜿蜒运动的动力学分析

为提高蛇形机器人执行各种运动的能力,研制了新型蛇形机器人系统．重点研究了该蛇形机器人的动力学．建立了机器人的运动学模型,并根据运动学模型提出了控制蛇形机器人蜿蜒运动的复合运动控制方法．用拉格朗日方法建立动力学模型,对不同参数下蛇形机器人的关节力矩特性和摩擦力特性进行了分析比较,为蛇形机器人的有效运动提供了理论依据．     

Analysis of creeping locomotion of a snake-like robot

Snakes perform many kinds of movement adapted to the environment. Utilizing the snake (its forms and motion) as a model to develop a snake-like robot, that performs the snake's function, is important for generating a new type of locomotion and expanding the possible uses of robots. In this study, we developed a simulator to simulate the creeping locomotion of the snake-like robot, in which the robot dynamics is modeled and the interaction with the environment is considered through Coulomb friction. This simulator makes it possible to analyze creeping locomotion with normaldirection slip, adding to the glide along the tangential direction. Through the developed simulator, we investigate the snake-like robot creeping locomotion which is generated only by swinging each of the joints from side to side and discuss the optimal creeping locomotion of the snake-like robot that is adapted to the environment.     

Smooth transition between different gaits of a hexapod robot via a central pattern generators algorithm

This paper focuses on the topic of smooth gait transition of a hexapod robot by a proposed central pattern generator (CPG) algorithm. Through analyzing the movement characteristics of the real insects, it is easy to generate kinds of gait patterns and achieve their smooth transition if we employ a series of oscillations with adjustable phase lag. Based on this concept, a CPG model is proposed, which is constructed by an isochronous oscillators and several first-order low-pass filters. As an application, a hexapod robot and its locomotion control are introduced by converting the CPG signal to robot’s joint space. Simulation and real world experiment are completed to demonstrate the validity of the proposed CPG model. Through measuring the position of the body center and the distance between footpoints and ground, the smooth gait transition can be achieved so that the effectiveness of the proposed method is verified.     

基于中枢模式发生器的仿生机器狗步态控制的应用研究

由于人工规划产生的步态是比较僵硬的、缓慢的,缺乏灵活的自组织能力,与真正的动物步态存在很大差别;文章提出了机器狗生物步态的概念;以生物的中枢模式发生器CPG模型为核心建立仿生四足机器狗运动控制系统;根据哺乳动物的肢体运动关系,建立机器狗膝髋关节运动关系方程,并设计系统软硬件;设计的控制器能够有效地克服机器狗关节轨迹跟踪控制中耦合、力矩非线性等因素的影响,且具有自适应能力;通过仿真验证了应用于机器狗的生物CPG控制机理的控制方法是有效的。     

基于人工势场与IB-LBM的机器蛇水中2D避障控制算法

为了提高多冗余度、多自由度机器蛇水下环境运动适应能力,提出了基于人工势场与IB-LBM （immersed boundary method-lattice Boltzmann method）相结合的机器蛇水中2D智能避障算法.首先,采用格子Boltzmann方法描述2D水中障碍模型、构造统一形式.然后,运用浸入边界法,结合现有的蛇形曲线运动方程,在计入人工势场法引力和斥力作用的情况下,推导得到机器蛇2D水中避障模型.之后,通过改变障碍影响距离、机器蛇摆动振幅、摆动频率、障碍点斥力增益系数、雷诺数以及目标点引力增益系数等重要参数,研究机器蛇在不同情况下的避障效率和避障安全性.最后,通过多次仿真求取各项参数的最优值.仿真结果表明,在各项参数都最优时,该算法能使机器蛇快速、安全、有效地避开水下复杂环境中的静态障碍而到达目标点.该方法不仅能够充分研究机器蛇在水中的流固耦合特性,获得实时避障效果,而且能够利用已知的环境信息生成最优路径.