Online Walking Pattern Generation and Its Application to a Biped Humanoid Robot — KHR-3 (HUBO)

The authors propose a simple on-line method for generating a walking pattern for the biped humanoid robot KHR-3 (HUBO). The problem of realizing a walking action in humanoid robots involves two components: generation of the basic walking pattern and the compensation required to maintain the robot's balance. Dynamic walking can be realized by incorporating the real-time stabilizing control algorithm developed for KHR-1, KHR-2 and KHR-3. The walking pattern of KHR-3 has four modes: forward/backward, left/right, curved walking and turning around. In the previous pattern generation of the KHR series, the step time and stride of the robot were fixed, and the walking modes, step time and action of stride without stopping could not be changed. Hence, the flexibility of the walking pattern of the robot needed to be upgraded. The walking pattern in this paper allows variation in the walking mode, step time and stride for each step. The pattern uses a simple mathematical form of trajectory curves, specifically the sine, cosine, linear and third-order polynomial curves, and the superposition of these curves is used to minimize the complexity and burden of the computation. The authors used a third-order polynomial to generate the trajectory of the robot's pelvis. With the aid of a simplified zero-moment point (ZMP) equation, the pelvis trajectories have a direct relationship with the ZMP trajectories. An effective means of generating the trajectories is introduced, and the scheme is verified experimentally under various walking conditions that take into account the step time and stride. The experimental platform, which has human-like features and movement, is briefly introduced here. With a simple kinematical structure and distributed control hardware architecture, the platform was designed to consume relatively low levels of energy. Moreover, the scheme for generating the trajectory is realized for variations to flexible walking.     

Realization of a hydraulic actuated biped robot walking without double support phase

This paper introduced a new walking pattern generation method for biped robots without active roll joint at the ankle and described a simple walking pattern generation method for the robot without using ZMP (Zero Moment Point) information directly. Firstly, the paper introduced a hydraulic actuated biped robot with eight degrees of freedom, which had payload capacity. Secondly, the paper provided a dynamic balance control method in the lateral plane. Not as the inverted pendulum model, this control method was also available for biped robot without active roll joint at the ankle. Thirdly, in order to decrease the vibration, the paper tried to keep the robot walking with an approximate constant speed in the frontal direction. Finally, weight loading experiments in the MD.DAMS simulation environment and physical prototype empty load experiments were used to verify the effectiveness of the proposed walking pattern methods.     

双足机器人预观控制的ZMP补偿步行模式研究

针对双足机器人的稳定行走,提出了一种预观控制的零力距点（ZMP）补偿步行模式在线生成方法。利用实际ZMP与目标ZMP之间的未来误差信息,基于预观控制计算机器人行走过程中质心的补偿量,事先调整质心轨迹来改变步态。最终使实际ZMP更好地跟踪目标值。12自由度的双足机器人动力学仿真验证了所提出方法的有效性,而且机器人能在一定程度不平整地面上实现稳定行走。     

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.     

双足机器人自然ZMP轨迹生成方法研究

为了实现双足机器人类人行走,提出了一种基于自然ZMP轨迹的双足机器人步行模式生成方法。在单腿支撑相,根据基于三维线性倒立摆模型,在设定从脚跟到脚趾移动的自然ZMP轨迹后,得到质心轨迹方程;在双腿支撑相采用线性摆模型生成质心轨迹方程。同时给出了在统一坐标系中的多步规划质心轨迹方程。在RoboCup 3D仿真平台实现了采用自然ZMP轨迹的双足机器人类人稳定步行,实验和竞赛结果都验证了该方法的有效性。     

仿人足底肌电特征的机器人行走规划

模仿人类行走规律是规划双足机器人运动的基础.以往模仿人类步态主要通过视觉方法或惯性模块测量(Inertia measurement unit, IMU)方法捕捉人体特征点轨迹.这些方法不考虑零力矩点(Zero moment point, ZMP)的相似性.为解决该问题,本文提出了一种基于足底肌电信号(Electromyography, EMG)和惯性模块测量信号的混合运动规划方法.该方法通过测量足底肌电信号计算出足底压力中心的位置以及踝关节扭矩,结合惯性模块所测量的人体躯干和双足轨迹,来规划双足机器人的步态.首先,用肌电仪测量足底肌电信号,用惯性测量模块测量人体各肢体部分的姿态轨迹,经数据标定后作为仿人机器人的运动参考; 然后,通过预观控制输出稳定的步态.为确保仿人行走的效果,基于人体相似性对运动数据进行了步态优化.实验验证和分析表明, EMG信号超前ZMP约160ms,利用这个特性实现了对压力点位置的有效预测,提高了机器人在线模仿人类行走的稳定性.     

基于全身协调的仿人机器人步行稳定控制

提出利用机器人质心（CoM）雅克比矩阵,实现全身协调补偿的算法。提出机器人的简化模型;分析基于CoM雅克比矩阵的补偿算法;采用CoM/ZMP（零点矩点）、减振和软着陆控制器实时控制双足步行,实现机器人全身协调的稳定控制;通过仿人机器人AFU09的双足步行实验证明该控制方法的有效性。     

Real-time continuous ZMP pattern generation of a humanoid robot using an analytic method based on capture point

This paper introduces an analytic method to generate a continuous ZMP pattern based on a capture point (CP). When a target CP is decided in real-time, the pattern generator makes the CP, ZMP, which it is within convex hull of the supporting feet area, and CoM patterns without discontinuity by closed-form solutions for a single step. Therefore, the proposed pattern generation method does not need a ZMP pattern modification, numerical iterations, and future ZMPs. The method is employed to treat applications such as step length change while walking and push recovery during walking in place. Furthermore, since compliant characteristics such as body oscillation appear in the humanoid robot, we introduce a system model, a double inverted pendulum model with flexible joints for the model-based control. Finally, the real-time walking pattern generation method and the walking control scheme are verified by experiments with the humanoid robot HUBO2.     

基于测力平台阵列的双足步行机器人实际零力矩点检测

提出一种多维力测力平台阵列系统,通过机器人行走过程中脚部与平台接触力的测量,并根据. vukobratovic关于ZMP的定义,得到机器人行走过程的ZMP实际轨迹信息,为双足步行机器人的稳态行走步态规划提 供参考依据.更进一步,该系统也可以用作双足步行机器人行走过程步态规划的实验平台.     

基于GCIPM行走的步行机器人路径规划

介绍了利用重力补偿倒立摆方式（GCIPM）提高步行机器人行走的稳定性。该方法与以往利用线性倒立摆方式（IPM）控制的机器人相似,但是考虑了期望轨迹上机器人的迈步腿力。当基于IPM的路径规划应用到实际的步行机器人上,依据ZMP控制理论从预固定点移动时,被忽略的迈步腿力的变化在实际中使稳定性得不到保证。由于GCIPM考虑了迈步腿力的影响,仿真表明,应用GCIPM的步行机器人,稳定性得到优化提高。     

Biped walking pattern generation by a simple three-dimensional inverted pendulum model

For three-dimensional (3D) walking control of a biped robot we analyze the dynamics of a 3D inverted pendulum in which motion is constrained to move along an arbitrarily defined plane. This analysis leads us to a simple linear dynamics, the Three-Dimensional Linear Inverted Pendulum Mode (3D-LIPM). The geometric nature of the trajectories under the 3D-LIPM and a method for walking pattern generation are discussed. A simulation result of a walking control using a 12-d.o.f. biped robot model is also shown.     

A novel compound biped locomotion algorithm for humanoid robots to realize biped walking

In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point （ZMP）. This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity （COG） of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot＇s collapse. Finally, the algorithm is validated by different kinds of simulation experiments.     

A walking pattern generation method of humanoid robot MAHRU-R

This paper proposes an omni-directional walking pattern generation method for a humanoid robot MAHRU-R. To walk stably without falling down, a humanoid robot needs the walking pattern. Our previous walking pattern method generated the walking pattern with linear polynomials of the zero moment point (ZMP). It implemented the simple walking like forward/backward walking, side step walking and turning. However, this method was not sufficient to satisfy the various walking which is combined by forward/backward walking, side step walking and turning. We needed to upgrade the walking pattern generation method to implement an omni-directional walking. We use the linear inverted pendulum model consisted of ZMP and center of mass in order to simplify the computation of walking pattern. The proposed method assumes that the state of the following stride is same to the state of the current stride. Using this assumption of walking pattern, the proposed method generates the stable walking pattern for various walking. And the proposed scheme generates the ZMP trajectory with the quartic polynomials in order to reduce the fluctuation of ZMP trajectory by various walking. To implement the efficient walking pattern, this method proposes three walking modules: periodic step module, transient step module and steady step module. Each step module utilizes weighted least square method with future ZMP position information. The effectiveness of the proposed method is verified by simulations of various walking. And the proposed method is confirmed by the experiment of real humanoid robot MAHRU-R.     

基于六维力／力矩传感器的拟人机器人实际ZMP检测

ZMP（Zero Moment Point)作为双足双行机器人动态稳定行走的判据,已应用于世界上银多著名的步行机器人系统。目前国外步行机器人大多采用力／力矩传感器进行ZMP的实际检测计算,但采用六维力／力矩传感器的却不多,而且其安装位置也各不同,国内机器人还都还都处于离线步态规划阶段,只进行理论了ZMP的计算,并没有进行实时检测。本文根据清华大学985重点项目“拟人机器人技术及其系统研究”的研究要求,确定基于六维力／力矩传感系统的实际ZMP检测方案,确这了传感器安装的最佳位置,推导了单脚支撑期,双脚支撑期的实际ZMP计算公式提出了基于ZMP理论的姿态调整方法,以期在实际应用中进行在线步态规划。     

Modular Architecture for Humanoid Walking Pattern Prototyping and Experiments

In this paper we describe the use of design patterns as a basis for creating humanoid walking pattern generator software having a modular architecture. This architecture enabled the rapid porting of several novel walking algorithms on a full-size humanoid robot, HRP-2. The body of work currently available allows extracting a general software architecture usable with inter-exchange between simulations and real experiments. The proposed architecture with the associated design patterns is described together with several applications: a pattern generator for a HRP-2 with passive toe joints, a pattern for dynamically stepping over large obstacles and a new quadratic problem (QP) formulation for the generation of the reference zero-momentum point. Thanks to the versatility and the modularity of the proposed framework, the QP method has been implemented and experienced within 4 days only.     

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。     

Demonstration and Analysis of Quadrupedal Passive Dynamic Walking

Animals, including human beings, can travel in a variety of environments adaptively. Legged locomotion makes this possible. However, legged locomotion is temporarily unstable and finding out the principle of walking is an important matter for optimum locomotion strategy or engineering applications. As one of the challenges, passive dynamic walking has been studied on this. Passive dynamic walking is a walking phenomenon in which a biped walking robot with no actuator walks down a gentle slope. The gait is very smooth (like a human) and much research has been conducted on this. Passive dynamic walking is mainly about bipedalism. Considering that there are more quadruped animals than bipeds and a four-legged robot is easier to control than a two-legged robot, quadrupedal passive dynamic walking must exist. Based on the above, we studied saggital plane quadrupedal passive dynamic walking simulation. However, it was not enough to attribute the result to the existence of quadrupedal passive dynamic walking. In this research, quadrupedal passive dynamic walking is experimentally demonstrated by the four-legged walking robot 'Quartet 4'. Furthermore, changing the type of body joint, slope angle, leg length and variety of gaits (characteristics in four-legged animals) was observed passively. Experimental data could not have enough walking time and could not change parameters continuously. Then, each gait was analyzed quantitatively by the experiment and three-dimensional simulation.     

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。     

Observer-based dynamic walking control for biped robots

This article presents a novel observer-based control system to achieve reactive motion generation for dynamic biped walking. The proposed approach combines a feedback controller with an online generated feet pattern to assure a stable gait. Using the desired speed of the robot, a preview control system derives the dynamics of the robot’s body, and thereby the trajectory of its center of mass, to ensure a zero moment point (ZMP) movement, which results in a stable execution of the calculated step pattern. Extending the control system by an observer, based on this knowledge and the measured sensor values, compensates for errors in the model parameters and disturbances encountering while walking.     

考虑综合步行约束的仿人机器人参数化3D 步态规划方法

给出了一种三维环境下双足行走的参数化步态规划方法,建立了仿人机器人13 质量块约束动力学模 型．考虑单腿支撑和双腿支撑无冲击连续切换的六点边界约束条件、可行步态物理约束条件以及ZMP 稳定性约束 条件,以关节输出力矩函数的二次型积分值最小作为优化指标,采用参数化步态优化方法,将复杂关节轨迹的规划 问题转化为分段多项式系数组成的有限参数向量的优化问题,得到了快速和慢速两组光滑无振动的优化步态．仿真 和样机实验验证了该方法的有效性．