双足机器人动态步行实时步态生成

针对双足机器人动态步行生成关节运动轨迹复杂问题,提出了一种简单直观的实时步态生成方案。建立了平面五杆双足机器人动力学模型,通过模仿人类步行主要运动特征并根据双足机器人动态步行双腿姿态变化的要求,将动态步行复杂任务分解为顺序执行的四个过程,在关节空间相对坐标系下设计了躯干运动模式、摆动腿和支撑腿动作及步行速度调整模式,结合当前步行控制结果反馈实时产生稳定的关节运动轨迹。仿真实验验证了该方法的有效性,简单易实现。     

一种基于迭代的质心逆运算的方法

通过已知质心精确反解计算仿人机器人各关节的角度是一个经常遇到的问题。在双足行走,平衡控制等领域都很常见。但对于自由度高的仿人机器人系统,质心逆运算比较困难,尤其在双足支撑情况下,问题变为一个多自由度的并联机构,此时需要额外的约束和限制条件,使得计算非常复杂。本文基于Levenberg-Marquardt算法来解决复杂关节的逆解问题,研究在给定踝关节的情况下,用假定质心固定身体上的简化模型来使得真实质心逼近目标点,然后通过重复逼近缩小误差。我们通过NAO仿人机器人模型上的模拟验证了该算法实现了较高的准确性和计算效率。     

Comparison of different gaits with rotation of the feet for a planar biped

Fast human walking includes a phase where the stance heel rises from the ground and the stance foot rotates about the stance toe. This phase where the biped becomes under-actuated is not present during the walk of humanoid robots. The objective of this study is to determine if this phase is useful to reduce the energy consumed in the walking. In order to study the efficiency of this phase, six cyclic gaits are presented for a planar biped robot. The simplest cyclic motion is composed of successive single support phases with flat stance foot on the ground. The most complex cyclic motion is composed of single support phases that include a sub-phase of rotation of the stance foot about the toe and of finite time double support phase. For the synthesis of these walking gaits, optimal motions with respect to the torque cost, are defined by taking into account given performances of actuators. It is shown that for fast motions a foot rotation sub-phase is useful to reduce the criteria cost. In the optimization process, under-actuated phase (foot rotation phase), fully-actuated phase (flat foot phase) and over-actuated phase (double support phase) are considered.     

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。     

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。     

Walking Control Algorithm of Biped Humanoid Robot on Uneven and Inclined Floor

This paper describes walking control algorithm for the stable walking of a biped humanoid robot on an uneven and inclined floor. Many walking control techniques have been developed based on the assumption that the walking surface is perfectly flat with no inclination. Accordingly, most biped humanoid robots have performed dynamic walking on well designed flat floors. In reality, however, a typical room floor that appears to be flat has local and global inclinations of about 2°. It is important to note that even slight unevenness of a floor can cause serious instability in biped walking robots. In this paper, the authors propose an online control algorithm that considers local and global inclinations of the floor by which a biped humanoid robot can adapt to the floor conditions. For walking motions, a suitable walking pattern was designed first. Online controllers were then developed and activated in suitable periods during a walking cycle. The walking control algorithm was successfully tested and proved through walking experiments on an uneven and inclined floor using KHR-2 (KAIST Humanoid robot-2), a test robot platform of our biped humanoid robot, HUBO.     

Experimental realization of dynamic walking of the biped humanoid robot KHR-2 using zero moment point feedback and inertial measurement

This paper describes a novel control algorithm for dynamic walking of biped humanoid robots. For the test platform, we developed KHR-2 (KAIST Humanoid Robot-2) according to our design philosophy. KHR-2 has many sensory devices analogous to human sensory organs which are particularly useful for biped walking control. First, for the biped walking motion, the motion control architecture is built and then an appropriate standard walking pattern is designed for the humanoid robots by observing the human walking process. Second, we define walking stages by dividing the walking cycle according to the characteristics of motions. Third, as a walking control strategy, three kinds of control schemes are established. The first scheme is a walking pattern control that modifies the walking pattern periodically based on the sensory information during each walking cycle. The second scheme is a real-time balance control using the sensory feedback. The third scheme is a predicted motion control based on a fast decision from the previous experimental data. In each control scheme, we design online controllers that are capable of maintaining the walking stability with the control objective by using force/torque sensors and an inertial sensor. Finally, we plan the application schedule of online controllers during a walking cycle according to the walking stages, accomplish the walking control algorithm and prove its effectiveness through experiments with KHR-2.     

Development of a Leg Part of a Humanoid Robot—Development of a Biped Walking Robot Adapting to the Humans' Normal Living Floor

The authors are engaged in studies of biped walking robots from thefollowing two viewpoints. One is a viewpoint as a human science. Theother is a viewpoint towards the development of humanoid robots.In this paper, the authors introduce an anthropomorphic dynamic bipedwalking robot adapting to the humans' living floor. The robot has tworemarkable systems: (1) a special foot system to obtain the positionrelative to the landing surface and the gradient of the surfaceduring its dynamic walking; (2) an adaptive walking control system toadapt to the path surfaces with unknown shapes by utilizing theinformation of the landing surface, obtained by the foot system. Twounits of the foot system WAF-3 were produced, a biped walking robotWL-12RVII that had the foot system and the adaptive walking controlsystem installed inside it was developed, and a walking experimentwith WL-12RVII was performed. As a result, dynamic biped walkingadapting to humans' floors with unknown shapes was realized. Themaximum walking speed was 1.28 s/step with a 0.3 m step length, andthe adaptable deviation range was from -16 to+16 mm/step in the vertical direction, and from-3 to +3° in the tilt angle.     

A Biologically Inspired Biped Locomotion Strategy for Humanoid Robots: Modulation of Sinusoidal Patterns by a Coupled Oscillator Model

Biological systems seem to have a simpler but more robust locomotion strategy than that of the existing biped walking controllers for humanoid robots. We show that a humanoid robot can step and walk using simple sinusoidal desired joint trajectories with their phase adjusted by a coupled oscillator model. We use the center-of-pressure location and velocity to detect the phase of the lateral robot dynamics. This phase information is used to modulate the desired joint trajectories. We do not explicitly use dynamical parameters of the humanoid robot. We hypothesize that a similar mechanism may exist in biological systems. We applied the proposed biologically inspired control strategy to our newly developed human-sized humanoid robot computational brain (CB) and a small size humanoid robot, enabling them to generate successful stepping and walking patterns.     

Hybrid control of biped robots to increase stability in locomotion

This article proposes a new hybrid control method, a combination of impedance control and computed‐torque control, to control biped robot locomotion. The former is used for the swinging (or unconstrained) leg and the latter for the supporting (or constrained) leg. This article also suggests that the impedance parameters be changed depending on the gait phase of the biped robot. To reduce the magnitude of the impact and to guarantee a stable footing during foot contact with the ground, the damping of the leg is increased drastically at the moment of contact. Computer simulations of a biped robot, with 3 DOF in each leg and the environment represented by a 3‐DOF environment model composed of linear and nonlinear compliant elements, were performed. Simulation results show that the performance of the proposed controller is superior to that of the computed‐torque controller, especially in reducing impact and stabilizing the footing. They also show that the proposed controller makes the biped robot more robust to the uncertainties in its own parameters as well as in its environment. © 2000 John Wiley & Sons, Inc.     

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。     

复杂环境下仿人机器人有效支撑区域的感知

当主流的仿人机器人都采ZMP(zero moment point)理论作为稳定行走的判据.实时ZMP点落在支撑足与地面接触形成的多边形支撑区域内是仿人机器人实现稳定步行的必要条件.因此实现仿人机器人在复杂现实环境中稳定行走,必须要求机器人足部感知系统提供足够丰富的地面环境信息,从而可以准确获取支撑区域的形状以实现基于实时ZMP点的稳定控制.文中将柔性阵列力传感器应用于仿人机器人足部感知系统,提出了获取仿人机器人支撑区域形状的方法,而且通过实验验证了其可行性.     

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。     

双足步行机器人动态直线步行运动的规划

本文对双足步行机器人迈步腿的质心做抛物线运动规划,使迈步腿产生垂直向上的惯性力,以平衡迈步腿自身的重量和身躯的一半重量.迈步期间的零矩点落在参考坐标系 X 轴向线上,完全避免了机器人侧向翻倒的可能性.文中采用了平行坐标架分配法,运动方程含义直观,简化了运动方程反解过程.     

Biped Locomotion by Reduced Ankle Power

Power reduction in the ankle joints of a biped robot is considered inthis paper. Ankles of human beings have small torque and are veryflexible within a certain range of motion (very stiff near and beyondthis range). This characteristic makes foot landing soft and gives agood contact between its sole and the ground. This feature can beimplemented in a biped robot by using a small actuator for the anklejoints. A small actuator consumes less energy and reduces the weightof the leg. With less power in the ankle joints, robot walkingbecomes more difficult to control. This problem can be solved byproviding a feedback control mechanism as presented in this paper. Thecontrol mechanism uses the motion of the body and the swinging leg toeliminate instability caused by the weak ankle. Two locomotionexamples, standing and walking, were investigated respectively toshow the validity of the proposed control scheme. In standing, thecontrol input is the displacement of the ankle joint of thesupporting leg. The control mechanism decides the bending angle ofthe body and the position of the swinging leg. For walking, only thebending angle of the body is used to avoid the discontinuity of thecontrol input. Experimental results are presented to show theeffectiveness of the control mechanism.     

Landing Force Control for Humanoid Robot by Time-Domain Passivity Approach

This paper proposes a control method to absorb the landing force or the ground reaction force for a stable dynamic walking of a humanoid robot. Humanoid robot may become unstable during walking due to the impulsive contact force of the sudden landing of its foot. Therefore, a control method to decrease the landing force is required. In this paper, time-domain passivity control approach is applied for this purpose. Ground and the foot of the robot are modeled as two one-port network systems that are connected, and exchange energy with each other. The time-domain passivity controller with admittance causality is implemented, which has the landing force as input and foot's position to trim off the force as output. The proposed landing force controller can enhance the stability of the walking robot from simple computation. The small-sized humanoid robot, HanSaRam-VII that has 27 DOFs, is developed to verify the proposed scheme through dynamic walking experiments.     

A closed-loop approach for tracking a humanoid robot using particle filtering and depth data

Humanoid robots introduce instabilities during biped march that complicate the process of estimating their position and orientation along time. Tracking humanoid robots may be useful not only in typical applications such as navigation, but in tasks that require benchmarking the multiple processes that involve registering measures about the performance of the humanoid during walking. Small robots represent an additional challenge due to their size and mechanic limitations which may generate unstable swinging while walking. This paper presents a strategy for the active localization of a humanoid robot in environments that are monitored by external devices. The problem is faced using a particle filter method over depth images captured by an RGB-D sensor in order to effectively track the position and orientation of the robot during its march. The tracking stage is coupled with a locomotion system controlling the stepping of the robot toward a given oriented target. We present an integral communication framework between the tracking and the locomotion control of the robot based on the robot operating system, which is capable of achieving real-time locomotion tasks using a NAO humanoid robot.     

Asymmetric trajectory generation and impedance control for running of biped robots

An online asymmetric trajectory generation method for biped robots is proposed to maintain dynamical postural stability and increase energy autonomy, based on the running stability criterion defined in phases. In a support phase, an asymmetric trajectories for the hip and swing leg of the biped robots is obtained from an approximated running model with two springless legs and a spring-loaded inverted pendulum model so that the zero moment point should exist inside the safety boundary of a supporting foot, and the supporting leg should absorb large reaction forces, take off and fly through the air. The biped robot is under-actuated with six degrees of under-actuation during flight. The trajectory generation strategies for the hip and both legs in a flight phase use the approximated running model and non-holonomic constraints based on the linear and angular momenta at the mass center. Next, we present an impedance control with a force modulation strategy to guarantee a stable landing on the ground and simultaneously track the desired trajectories where the desired impedance at the hip link and both legs is specified. A series of computer simulations for two different types of biped robots show that the proposed running trajectory and impedance control method satisfy the two conditions for running stability and make the biped robot more robust to variations in the desired running speed, gait transitions between walking and running, and parametric modeling errors. We have examined the feasibility of this method with running experiments on a 12-DOF biped robot without arms. The biped robot could run successfully with average forward speed of about 0.3359 [m/s]. Electronic Supplementary Material  The online version of this article () contains supplementary material, which is available to authorized users.

Adaptive splitbelt treadmill walking of a biped robot using nonlinear oscillators with phase resetting

To investigate the adaptability of a biped robot controlled by nonlinear oscillators with phase resetting based on central pattern generators, we examined the walking behavior of a biped robot on a splitbelt treadmill that has two parallel belts controlled independently. In an experiment, we demonstrated the dynamic interactions among the robot mechanical system, the oscillator control system, and the environment. The robot produced stable walking on the splitbelt treadmill at various belt speeds without changing the control strategy and parameters, despite a large discrepancy between the belt speeds. This is due to modulation of the locomotor rhythm and its phase through the phase resetting mechanism, which induces the relative phase between leg movements to shift from antiphase, and causes the duty factors to be autonomously modulated depending on the speed discrepancy between the belts. Such shifts of the relative phase and modulations of the duty factors are observed during human splitbelt treadmill walking. Clarifying the mechanisms producing such adaptive splitbelt treadmill walking will lead to a better understanding of the phase resetting mechanism in the generation of adaptive locomotion in biological systems and consequently to a guiding principle for designing control systems for legged robots.     

Balancing of humanoid robot using contact force/moment control by task-oriented whole body control framework

Balancing control of humanoid robots is of great importance since it is a necessary functionality not only for maintaining a certain position without falling, but also for walking and running. For position controlled robots, the for-ce/torque sensors at each foot are utilized to measure the contact forces and moments, and these values are used to compute the joint angles to be commanded for balancing. The proposed approach in this paper is to maintain balance of torque-controlled robots by controlling contact force and moment using whole-body control framework with hierarchical structure. The control of contact force and moment is achieved by exploiting the full dynamics of the robot and the null-space motion in this control framework. This control approach enables compliant balancing behavior. In addition, in the case of double support phase, required contact force and moment are controlled using the redundancy in the contact force and moment space. These algorithms are implemented on a humanoid legged robot and the experimental results demonstrate the effectiveness of them.