基于虚拟模型的四足机器人对角小跑步态控制方法

为提高四足机器人对角小跑运动的稳定性,实现机器人躯干6维运动方向控制的解耦,提出了一种基于虚拟模型的对角小跑步态控制方法.控制器主要包括支撑相虚拟模型控制和摆动相虚拟模型控制.在支撑相,建立了作用于躯干质心的虚拟力与对角支撑腿关节扭矩之间的数学关系,通过调整躯干虚拟力的大小控制躯干的高度与姿态,控制机器人前进速度和自转角速度.在摆动相,将机器人侧向速度控制引入到足端轨迹规划中,并通过虚拟的"弹簧-阻尼"元件驱动摆动足沿给定轨迹运动.此外,在控制器设计过程中,引入了状态机,用于监控机器人各腿的状态,并输出对角小跑步态相位切换指令.仿真实验结果表明,机器人能够以对角小跑步态在平地上进行全方位移动,跨越不平坦地形,并能够抵抗外部冲击,证明了文中控制方法的有效性和鲁棒性.     

四足机器人对角小跑步态全方位移动控制方法及其实现

为实现四足机器人在平面和斜坡上的全方位移动,提出了基于对角小跑步态的运动控制方法.基于所推导的四足机器人运动学方程和仿生步态规划方法,将机器人在平面内的运动解耦为前向运动、侧向运动和自转运动3部分以降低运动控制的复杂度.首先利用各部分振荡幅度来实现机器人在3个方向上的运动速度控制,然后利用将各部分运动合成实现四足机器人在水平面内的全方位移动控制;基于平面的全方位移动控制方法,对足端位置进行映射,实现了机器人在斜坡上的对角小跑步态全方位运动控制.最后,分别在平面和斜坡上进行了仿真和实际物理样机实验.步程计数据、仿真数据与物理样机实验结果之间的差别在可接受范围之内,证实了该方法有效地实现了机器人的速度控制和运动解耦,验证了所提出方法的正确性和有效性.     

具有弹性连杆机构的四足机器人对角小跑步态控制

为了提高四足机器人的运动性能和抗冲击能力,设计了一种具有弹性连杆机构和线驱动系统的四足机器人,称为LCS(linkage-cable-spring)四足机器人.借鉴SLIP (弹簧负载倒立摆)模型,提出了基于着地角的速度控制策略和基于能量补偿的质心高度控制策略.采用姿态控制策略来提高对角小跑步态的运动稳定性.仿真实现了给定前进速度条件下稳定的对角小跑步态.搭建LCS四足机器人样机实验平台,完成了踏步、对角小跑步态行走实验.实验结果表明,LCS四足机器人运动过程中机身翻滚和俯仰角能控制在2?以内,并能平稳通过10 mm×10 mm小型障碍物.     

四足机器人对角小跑步态下液压驱动单元位置伺服控制特性参数灵敏度研究

高性能四足仿生机器人的关节由高度集成的液压驱动单元(HDU)驱动,液压传动的引入在带来高性能的同时,也增强了非线性和参数时变性等问题,此外机器人各关节复杂多变的载荷特性,也增大了每个关节HDU的控制难度.为了有针对性地进行对角小跑步态的控制补偿,研究了各HDU位置控制特性的主要影响参数.首先,考虑伺服阀动态特性、压力-流量非线性、伺服缸活塞初始位移及摩擦非线性,搭建其位置伺服控制系统.基于HDU实际结构参数和工作参数建立仿真模型.将HDU实测的摩擦力及对角小跑步态下各关节实测的位移与外负载力数据加载至仿真模型中,得出HDU伺服控制的输出位移及负载力仿真曲线,并进行了试验验证.基于位置伺服控制方程,推导含非线性和时变参数的灵敏度方程表达式,进而求解4个关节工况下HDU输出位移对各参数的灵敏度函数.以采样时间内参数变化引起输出变化的最大值及参数变化引起输出变化绝对值的总和为灵敏度衡量指标,给出指标变化柱形图,分析各参数灵敏度变化规律,并对各HDU中供油压力、比例增益、活塞初始位移及外负载力4个参数的灵敏度指标进行试验验证.最后得到了对角小跑步态下影响各关节HDU位置控制特性的主要和次要影响参数,为位置补偿控制器的设计提供了参考.     

四足机器人对角小跑起步姿态对稳定步行的影响

对四足机器人对角小跑步态下绕支撑对角线的翻转力矩建立了力学模型，分析了该力矩对机器人运动姿态及稳定步行的不利影响，并提出了利用起步姿态来削弱翻转力矩不利影响的方法——三分法．     

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。     

基于倒立摆模型的四足机器人对角步态规划

为提高点着地四足机器人在匀速对角小跑过程中的动态稳定性,将对角小跑过程简化为一个倒立摆模型。;针对四足机器人对角小跑过程中由于重心无法始终处于支撑对角线上所引起的翻转,在此模型中转换为由于重心引起的摆动角误差;采用虚位移原理对机器人摆动角的变化进行分析,确定不同重心运动变化对摆动角误差的影响并找到合适的重心起始位置,理论上能够使摆动角的误差为零;动态仿真实验验证了所提出的对角步态规划能够使四足机器人实现稳定的对角小跑的有效性。     

液压驱动伺服机器人的模糊滑模控制研究

针对液压驱动四足机器人伺服系统非线性和不确定性严重的问题,提出了一种快速响应、鲁棒性好、控制精度高的模糊滑模控制器,并进行了仿真研究.首先,建立了液压驱动伺服机器人的液压动力机构非线性数学模型,利用Lyapunov方法设计了滑模控制器;其次,构造了一个模糊边界层宽度调节器,削弱滑模控制的抖振;最后,分析了参考力、液压参数、供油压力及负载刚度变化对系统输出的影响.仿真结果表明,该控制器对液压伺服力系统非线性和参数变化具有较好的控制效果.该方法用于四足液压驱动伺服机器人的控制是可行的、有效的.     

仿生四足机器人设计及运动学足端受力分析

仿生四足机器人腿部结构设计与生物腿部实际结构存在差异,足端与地面的刚性接触力对于控制其运动平稳和收敛会产生不利影响。为解决上述问题,分析德国牧羊犬骨骼结构,通过图像处理和分析手段获取牧羊犬对角小跑步态运动中四肢各关节的运动规律,设计一款四足机器人。该机器人足端具有转化足端与地面刚性接触为柔性接触的机构。根据正运动学和逆运动学理论分析模型足端工作空间。将仿真获得的受力曲线与实际受力曲线进行对比,结果表明,运动控制函数和柔性机构更有助于四足机器人的运动平稳。     

基于扩展雅可比矩阵的冗余液压驱动四足机器人运动控制

针对冗余液压驱动四足机器人运动学逆解问题,提出一种基于扩展雅可比矩阵的冗余液压驱动四足机器人运动控制方法.该方法既能解决冗余自由度带来的逆解多解问题,还能使机器人足端入地角度满足摩擦锥要求避免足端滑动.首先,规划机器人足端轨迹得到机器人足端速度,在分析机器人足端入地角度对机器人运动性能影响的基础上,结合机器人腿部结构几何关系,建立扩展雅可比矩阵,确立机器人关节角度速度和足端速度的映射关系,即得到机器人关节角度的解.然后,在对角步态下,通过仿真对传统的梯度投影法和提出的扩展雅可比矩阵法进行对比,理论分析及仿真表明传统的梯度投影法存在误差累积,且在实时性上不如扩展雅可比矩阵法.最后,实验验证了基于扩展雅可比矩阵逆运动学分析方法的可行性和有效性.     

带主动腰关节的四足机器人平稳运动控制

针对四足机器人在对角小跑运动时出现的后腿“拖地”、机体振荡的现象,提出了一种基于偏航方向上主动腰关节摆动的解决方法。通过D-H法对机器人各关节进行运动学建模,获得其运动学方程,并采用Kuramoto振荡器模型作为扩展的CPG耦合网络振子,实现对腰、腿关节的统一控制。仿真实验表明,经过腰关节控制优化后的机器人在对角小跑时,相对于刚体躯干的机器人,姿态角变化幅度显著减小,抬腿高度明显增加,有效地提高了机器人的运动稳定性,证明了方法的可行性。     

Torso motion control and toe trajectory generation of a trotting quadruped robot based on virtual model control

This article presents an intuitive approach based on virtual model control for robust quadrupedal trotting. The controller consists of two main modules: support phase virtual model control for torso motion control and flight phase virtual model control for flight toe trajectory generation. We mapped the relationship between the joint torques of support legs and the torso forces. And virtual forces are applied to the torso to regulate the attitude, height, and velocities of the torso during support phase. To unify the control law, virtual forces are also applied to flight toes to track the planned trajectories that are designed based on lateral velocity of the torso and contact signals of the legs. Moreover, state machine, terrain estimator, and the high level controller are designed to control the robot trotting. Simulations of quadruped trotting versatilely on flat ground, trotting over stairs and slops as well as the impact recovery are reported to demonstrate the effectiveness and robustness of our controller.     

Energy-optimal gait analysis of quadruped robots

It is important for walking robots such as quadruped robots to have an efficient gait. Since animals and insects are the basic models for most walking robots, their walking patterns are good examples. In this study, the walking energy consumption of a quadruped robot is analyzed and compared with natural animal gaits. Genetic algorithms have been applied to obtain the energy-optimal gait when the quadruped robot is walking with a set velocity. In this method, an individual in a population represents the walking pattern of the quadruped robot. The gait (individual) which consumes the least energy is considered to be the best gait (individual) in this study. The energy-optimal gait is analyzed at several walking velocities, since the amount of walking energy consumption changes if the walking velocity of the robot is changed. The results of this study can be used to decide what type of gait should be generated for a quadruped robot as its walking velocity changes. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001.     

Generation and Analyses of the Reinforced Wave Gait for a Mammal-Like Quadruped Robot

The statically stable gait control of a mammal-like quadruped robot that provides an adequate or stable manner of traversing over irregular terrain was addressed. The reinforced wave gait which integrates new parameters of the lateral offset and displacements of the center of gravity (COG) based on the profiles of standard wave gait was investigated. The continuous and discontinuous motion trajectory of a robot’s COG in the periodic reinforced wave gait could be realized. The longitudinal and lateral stability margins of a reinforced wave gait were formulated for the gait generation and control of a quadruped robot. Moreover, the effects of the lateral offset on the stability, velocity and the energy efficiency were studied in details. The reinforced wave gait with lateral sway motion adequately improved the stability, and two particular gait patterns that involve the lateral sway motion for a maximal velocity and maximum achievable stability were described. With consideration of a quadruped robot with asymmetric carrying loads on its body, a scheme that relates to the gait parameters of the displacement of a robot’s COG to avoid losing stability was proposed. The simulation and experimental results about the effects of lateral offset added in the reinforced wave gait on the minimum power consumption during a quadruped robot walking on a flat terrain indicated that the reinforced wave gait with a larger lateral offset would generate a better wave gait with a higher velocity and energy efficiency.     

Quadruped robot trotting over irregular terrain assisted by stereo-vision

Legged robots have the potential to navigate in challenging terrain, and thus to exceed the mobility of wheeled vehicles. However, their control is more difficult as legged robots need to deal with foothold computation, leg trajectories and posture control in order to achieve successful navigation. In this paper, we present a new framework for the hydraulic quadruped robot HyQ, which performs goal-oriented navigation on unknown rough terrain using inertial measurement data and stereo-vision. This work uses our previously presented reactive controller framework with balancing control and extends it with visual feedback to enable closed-loop gait adjustment. On one hand, the camera images are used to keep the robot walking towards a visual target by correcting its heading angle if the robot deviates from it. On the other hand, the stereo camera is used to estimate the size of the obstacles on the ground plane and thus the terrain roughness. The locomotion controller then adjusts the step height and the velocity according to the size of the obstacles. This results in a robust and autonomous goal-oriented navigation over difficult terrain while subject to disturbances from the ground irregularities or external forces. Indoor and outdoor experiments with our quadruped robot show the effectiveness of this framework.     

基于重心动力学及虚拟模型的负载型四足步行平台对角步态控制方法

为提高负载型四足步行平台对角步态行走的稳定性,减小较大的腿部质量及偏心质量对稳定行走的影响,提出融合重心动力学及虚拟模型的控制方法．应用虚拟模型控制方法对机身及摆动腿加速度进行求解．结合平台重心动力学模型得到其所受合外力,而后应用二次规划将平台合外力分配到支撑腿足端．接着运用逆向动力学和关节空间PD控制得到步行平台关节力矩．通过Adams和Simulink对负载型四足步行平台对角步态行走进行仿真,并将该方法与虚拟模型控制算法进行对比．结果表明重心动力学及虚拟模型控制方法能够使平台姿态角稳定在目标值附近,在平台受到侧向冲击情况下横滚角、俯仰角分别减小约42%、21.8%,在机身偏心全向行走过程中减小50%、89%．证明了所提控制方法能够有效应对较大的腿部质量及偏心质量的影响,提高负载型四足步行平台对角步态行走的稳定性和鲁棒性．     

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

This paper proposes a new adaptive trajectory tracking control scheme of the wheeled mobile robot without longitudinal velocity measurement. First, based on a kinematic controller, we obtain a new tracking error equation, which is suitable to develop an adaptive controller. Then, we develop a new adaptive trajectory tracking controller, which does not need any accurate values of the wheeled mobile robot parameters, including the driving motor parameters. Moreover, as the longitudinal velocity measurement is still difficult, this controller is developed without longitudinal velocity measurement. In addition, this new adaptive controller introduces a method to improve the control performance. The stability of the closed‐loop system is presented using the direct Lyapunov method. Finally, numerous simulations verify the effectiveness of the new controller.     

Central pattern generator based reflexive control of quadruped walking robots using a recurrent neural network

This paper presents a novel Central Pattern Generator (CPG) model for controlling quadruped walking robots. The improvement of this model focuses on generating any desired waveforms along with accurate online modulation. In detail, a well-analyzed Recurrent Neural Network is used as the oscillators to generate simple harmonic periodic signals that exhibit limit cycle effects. Then, an approximate Fourier series is employed to transform those mentioned simple signals into arbitrary desired outputs under the phase constraints of several primary quadruped gaits. With comprehensive closed-form equations, the model also allows the user to modulate the waveform, the frequency and the phase constraint of the outputs online by directly setting the inner parameters without the need for any manual tuning. In addition, an associated controller is designed using leg coordination Cartesian position as the control state space based on which stiffness control is performed at sub-controller level. In addition, several reflex modules are embedded to transform the feedback of all sensors into the CPG space. This helps the CPG recognize external disturbances and utilize inner limit cycle effect to stabilize the robot motion. Finally, experiments with a real quadruped robot named AiDIN III performing several dynamic trotting tasks on several unknown natural terrains are presented to validate the effectiveness of the proposed CPG model and controller.     

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。