伸缩腿双足机器人半被动行走控制研究

研究半被动伸缩腿双足机器人行走控制和周期解的全局稳定性问题.使用杆长可变的倒立摆机器人模型,以支撑腿的伸缩作为行走动力源,采用庞加莱映射方法分析了双足机器人行走的不动点及其稳定性.当脚与地面冲击时,假设两腿间的夹角保持为常数,设计了腿伸缩长度的支撑腿角度反馈控制率.证明了伸缩腿双足机器人行走过程不动点的全局稳定性.仿真结果表明,本文提出的腿伸缩长度反馈控制可以实现伸缩腿双足机器人在水平面上的稳定行走,并且周期步态对执行器干扰和支撑腿初始角速度干扰具有鲁棒性.     

半被动双足机器人的准开环控制

目前的被动行走机器人还只能完成单一的步态,且非常容易摔倒,为此对半被动双足机器人的稳定行走控制问题进行了研究．通过结合被动行走和主动控制两种原理的优点,提出了一种准开环的行走控制方法．通过检测安装在机器人足底和髌骨处的接触开关信号,在髋关节处施加一个间断的、微小的开环振荡力矩,进而实现高效的稳定步行．仿真结果表明,当控制参数在较大范围内变化时,双足机器人仍可实现稳定行走,且步行能耗特性与人类相似;通过调节振荡力矩的参数,机器人可实现稳定的行走模式转换．     

半被动双足机器人控制系统设计

由于双足机器人行走是单腿支撑和双腿支撑交替进行的过程,同时只有在与行走过程相应的控制策略不断变化时(最优控制),双足机器人才能自然稳定地行走,因此,控制起来很困难。针对现有双足机器人控制系统方面的不足,提出了一种通过舵机驱动提供冲击力矩的半被动双足机器人控制系统方案,即由一个上位机(PC机)和一个控制器构成控制系统,通过USB进行高速数据通信。上位机主要负责系统监控和协调控制;控制器采用STM32处理器,实现机器人的三个关节的数据采集、步态规划逻辑运算以及向上位机传送相应的运动状态数据。测试结果表明,当存在一些干扰时,控制系统通过传感器检测到的实时数据是准确可靠的,并且能很好地控制半被动双足机器人行走。     

基于脉冲推力的半被动双足机器人无模型神经网络控制

研究了半被动双足机器人的平面稳定行走控制问题。以最简行走模型为动力学模型,采用沿支撑腿方向的脚后跟脉冲推力作为行走动力源。考虑到系统模型的非线性特征,将基于三角函数扩展的函数链接型人工神经网络控制算法引入到机器人系统中,以产生系统所需的脉冲推力。并采用基于数据驱动的无模型同步扰动随机逼近算法对神经网络的权值进行更新。利用庞加莱映射方法分析了半被动双足机器人行走的稳定条件。在理论分析的基础上,对该算法进行了仿真研究。仿真结果表明：文中所提算法在收敛快速性上要优于迭代学习控制算法,可以实现双足机器人平面上的稳定周期行走。且雅可比矩阵的特征值均位于单位圆内,满足系统的稳定条件。     

双足机器人稳定行走的仿人预测控制研究

针对双足机器人的稳定行走,提出了一种新的仿人预测控制在线步行模式生成方法。把期望零力矩点（ZMP）分解成离线规划好的参考ZMP和实时变化的可变ZMP之和,通过预测控制和其逆系统共同作用对质心运动进行控制,从而生成具有自适应性的步行模式。但单一的预测控制系统对诸如矩形齿状扰动的可变ZMP的跟踪存在较大的误差,结合仿人智能控制对误差的强抑制能力,设计了与预测控制相结合的仿人预测控制系统。仿真实验验证对矩形齿状扰动的可变ZMP,仿人预测系统也能实现较好的跟踪。     

仿人机器人双足行走模型研究

针对仿人机器人双足行走的稳定性问题,引入零力矩点理论,根据稳定行走必须满足地面反作用力位于稳定区域内这个条件,推导出仿人机器人在行走过程中单双腿支撑期的稳定区域面积和稳定裕量。建立2种不同形状的仿人机器人双足模型,在足底和地面间创建一系列接触力,并通过机械系统动力学自动分析软件得到行走过程中足底各个点的受力曲线并进行受力分析,得出合理的双足形状。     

仿人预测控制在双足机器人步行控制中的应用

基于零力矩点(ZMP)的预测控制是目前双足机器人步行控制中最先进的方法,但是预测控制需要比较精确的预测模型,在环境扰动导致模型失配时,预测控制的性能下降较快。为了解决这个问题,利用仿人智能控制对环境误差具有较强抑制的特点改进预测控制。探讨了在步行控制中引入仿人智能控制的必要性和仿人智能控制改进预测控制的可行性,并设计了仿人预测控制器。最后通过仿真实验验证了新的控制器对双足机器人步行控制的有效性。     

脉冲推力作用下半被动双足机器人的行走动力学分析

为了提高半被动双足机器人在水平地面上行走的稳定性,研究一种脉冲推力作用下半被动双足机器人的行走动力学行为.以最简单的特殊行走模型为动力学模型,采用支撑腿脚后跟脉冲推力作为双足机器人行走动力源.鉴于系统模型的高度非线性,将连续阶段的非线性微分方程线性化;利用角动量守恒和脉冲推力构造一个二维离散映射;采用离散映射的不动点及其特征值分析系统周期步态的存在性和稳定性;接着讨论系统的倍周期分岔.在理论分析的基础上,通过Matlab软件对半被动双足机器人的行走动力学进行仿真实验. 仿真结果表明,在水平地面上行走的半被动双足机器人具有稳定的周期-1步态和周期-2步态.     

移动可伸缩三维倒立摆模型的双足机器人步态控制策略

双足机器人的步态控制策略是保证双足稳定行走的重要条件之一.结合人在行走时ZMP平稳移动的特性,建立了一种移动可伸缩三维倒立摆模型;在约束平面内分析ZMP与COG的运动关系,将ZMP和COG分别定为快变因子和慢变因子,提出了移动可伸缩三维倒立摆模型的双足机器人步态控制策略;最后通过Matlab/ADAMS进行了步态控制仿真研究.仿真结果表明双足机器人可以稳定地行走,验证了该步态控制策略的可行性.     

基于神经网络的仿人跑步机器人步态规划

为了快速生成仿人机器人跑步运动轨迹,研究了一种用于仿人机器人跑步步态生成的步态规划器。采用三维弹簧倒立摆模型描述跑步过程中仿人机器人质心运动规律,奔跑时机器人质心轨迹及落脚点位置可以由四个步态参数来确定,从而将步态规划问题转化成步态参数优化问题,求解了500余种不同运动状态下的步态参数。建立了基于三层BP神经网络的步态规划器,将优化结果作为训练样本训练神经网络。用上述规划器实现了仿人机器人跑步步态规划并对规划结果进行了仿真验证。研究结果表明,基于BP神经网络的步态规划器可以实现步态参数的快速计算,生成的跑步步态逼真;提出的跑步运动步态规划方法可行,为仿人机器人实时轨迹生成提供了一种解决方法。     

Development of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems

This paper presents a novel design of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems.The proposed approach implements a novel strategy to achieve stable bipedal walk by decoupling the walking motion control from the sideway balancing control.This strategy allows the walking controller to execute the walking task independently while the sideway balancing controller continuously maintains the balance of the robot.The hip-mass carry approach and selected stages of walk implemented in the control strategy can minimize the efect of major hip mass of the robot on the stability of its walk.In addition,the developed smooth joint trajectory planning eliminates the impacts of feet during the landing.In this paper,the new design of mechanism for locomotion systems and balancing systems are introduced.An additional degree of freedom introduced at the ankle joint increases the sensitivity of the system and response time to the sideway disturbances.The efectiveness of the proposed strategy is experimentally tested on a bipedal robot prototype.The experimental results provide evidence that the proposed strategy is feasible and advantageous.     

仿人机器人动态步行控制综述

综述了仿人机器人动态步行的研究历史和研究现状。归纳了动态步行的特点,分析了动态步行稳定性判定方法,介绍了基于ZMP的姿态稳定判据和基于庞加莱映射（Poincaré Map）的步态稳定判据。总结了仿人机器人学习适应复杂地面环境步行的方法,概述了动态步行控制实现的典型解决方案,指出了动态步行控制中待解决的问题,并探讨了未来的发展方向。     

变长度柔性双足机器人行走控制及稳定性分析

针对传统双足机器人模型缺少脚质量和躯干的问题,提出考虑摆动腿动态及躯干影响的柔性双足机器人模型,并对其行走控制及稳定性进行研究。首先,建立系统的动力学模型并采用欧拉-拉格朗日法推导了系统的动力学方程;同时,在弹簧负载倒立摆（SLIP）模型的基础上添加刚性躯干、脚质量及采用变长度伸缩腿,充分考虑躯干及摆动腿动力学对机器人行走步态的影响;其次,设计基于变长度腿的反馈线性化控制器来跟踪目标轨迹,以及调节摆动腿和躯干的姿态;最后,利用Newton-Raphson迭代法和庞加莱映射分析机器人的不动点及轨道稳定性条件,并在理论分析的基础上进行仿真。仿真结果表明,所提控制器可以实现机器人的周期行走,对外界干扰具有良好的鲁棒性,且雅可比矩阵所有特征值的模均小于1,能形成稳定的极限环,证明系统是轨道稳定的。     

双足步行机器人能量成型控制

为了使双足被动行走机器人的行走步态符合仿生规律,且当路面坡度变化后,迅速进入新的稳定步态行走,提出了角度不变能量成型控制策略.研究了欠驱动双足机器人能量匹配条件和能量成型控制器的求解;由于动能相对于旋转变换不具有对称性,通过在能量成型控制中附加一个辅助控制量,实现角度不变控制.仿真结果表明,该算方法可实现仿生控制,既能扩大吸引域,又改善系统的鲁棒性.     

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.     

Stability and control of dynamic walking for a five-link planar biped robot with feet

During dynamic walking of biped robots, the underactuated rotating degree of freedom （DOF） emerges between the support foot and the ground, which makes the biped model hybrid and dimension-variant. This paper addresses the asymptotic orbit stability for dimension-variant hybrid systems （DVHS）. Based on the generalized Poincare map, the stability criterion for DVHS is also presented, and the result is then used to study dynamic walking for a five-link planar biped robot with feet. Time-invariant gait planning and nonlinear control strategy for dynamic walking with fiat feet is also introduced. Simulation results indicate that an asymptotically stable limit cycle of dynamic walking is achieved by the proposed method.     

Stability and control of dynamic walking for a five-link planar biped robot with feet

During dynamic walking of biped robots, the underactuated rotating degree of freedom (DOF) emerges between the support foot and the ground, which makes the biped model hybrid and dimension-variant.This paper addresses the asymptotic orbit stability for criterion for DVHS is also presented, and the result is then used to study dynamic walking for a five-link planar biped robot with feet. Time-invariant gait planning and nonlinear control strategy for dynamic walking with flat feet is also introduced. Simulation results indicate that an asymptotically stable limit cycle of dynamic walking is achieved by the proposed method.     

Level-ground walking for a bipedal robot with a torso via hip series elastic actuators and its gait bifurcation control

Recent studies have shown that a bipedal robot with a torso supported by springs on the hip can have a stable passive gait on a slope, while such a robot walking on level ground is a new challenge and has rarely been studied. This research adds actuators in series with the springs to form series elastic actuators on the hip and applies a state machine as controller to achieve stable walking on level ground. During walking, hip series elastic actuators support the torso from the legs as well as complement the energy to the system via elastic potential energy. The state machine uses the landing impact of the swing leg and the actuation durations as events to make the robot switch between successive active and passive walking processes. Because this simple scheme makes full use of the dynamics of the robot, it can lead to an efficient and natural gait. By means of numerical simulation, in addition to the stable period-1 gait, we found a variety of gait bifurcation phenomena, including the period-doubling bifurcation, the Neimark–Sacker bifurcation, the Neimark–Sacker-2 bifurcation, the period-X bifurcation, and the Neimark–Sacker-X bifurcation, among which many types have never been reported in previous studies. We also show that the unstable period-1 gait embedded in the bifurcation gait can be stabilized by applying the Ott–Grebogi–Yorke method. Not only can the gait bifurcation be suppressed, but also higher gait performance can be achieved.     

Selection of two arm-swing strategies for bipedal walking to enhance both stability and efficiency

Walking ability, which involves mainly stability and efficiency, is one of the most important issues in humanoid robots. Effective use of a robot’s arms is expected to improve its walking ability under its body constraints. Although several types of arm-swing strategies have been proposed, they are difficult to execute simultaneously. We propose two-stage integration of these strategies to enhance both stability and efficiency. A selection algorithm for locomotion (SAL) selects the appropriate strategy according to the demands of the situation. In the first stage, two strategies are evaluated. One of them, Ro-SAL, entails use and compensation of the moment of the swing leg by hip rotation and arm swing. The other strategy, Su-SAL, entails the support of center of gravity trajectory tracking based on a predictive control. Ro-SAL is effective for the stable state and states with internal model error, whereas Su-SAL is effective in states with external force and environmental complexity. In the second stage of the proposed method (AS-SAL), the robot recognizes the current state and selects the optimal combination of the two arm-swing strategies. As a result, a humanoid robot can exhibit more efficient, stable bipedal walking without falling.