Position-based impedance control of a biped humanoid robot

This paper describes position-based impedance control for biped humanoid robot locomotion. The impedance parameters of the biped leg are adjusted in real-time according to the gait phase. In order to reduce the impact/contact forces generated between the contacting foot and the ground, the damping coefficient of the impedance of the landing foot is increased largely during the first half double support phase. In the last half double support phase, the walking pattern of the leg changed by the impedance control is returned to the desired walking pattern by using a polynomial. Also, the large stiffness of the landing leg is given to increase the momentum reduced by the viscosity of the landing leg in the first half single support phase. For the stability of the biped humanoid robot, a balance control that compensates for moments generated by the biped locomotion is employed during a whole walking cycle. For the confirmation of the impedance and balance control, we have developed a life-sized humanoid robot, WABIAN-RIII, which has 43 mechanical d.o.f. Through dynamic walking experiments, the validity of the proposed controls is verified.     

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。     

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.     

Online Balance Controllers for a Hopping and Running Humanoid Robot

This paper describes online balance controllers for running in a humanoid robot and verifies the validity of the proposed controllers via experiments. To realize running in the humanoid robot, the overall control structure is composed of an offline controller and an online controller. The main purpose of the online controller is to maintain dynamic stability while the humanoid robot hops or runs. The online controller is composed of the posture balance control in the sagittal plane, the transient balance control in the frontal plane and the swing ankle pitch compensator in the sagittal plane. The posture balance controller makes the robot maintain balance using an inertial measurement unit sensor in the sagittal plane. The transient balance controller makes the robot keep its balance in the frontal plane using gyros attached to each upper leg. The swing ankle pitch compensator prevents the swing foot from hitting the ground at unexpected times while the robot runs forward. HUBO2 was used for the running experiment. It was designed for the running experiment, and is lighter and more powerful than the previous walking robot platform, HUBO. With the proposed controllers, HUBO2 ran forward stably at a maximum speed of 3.24 km/h and this result verified the effectiveness of the proposed algorithm. In addition, in order to show the contribution of the stability, the running performance according to the existence of each controller was described by experiment.     

Posture/Walking Control for Humanoid Robot Based on Kinematic Resolution of CoM Jacobian With Embedded Motion

This paper proposes the walking pattern generation method, the kinematic resolution method of center of mass (CoM) Jacobian with embedded motions, and the design method of posture/walking controller for humanoid robots. First, the walking pattern is generated using the simplified model for bipedal robot. Second, the kinematic resolution of CoM Jacobian with embedded motions makes a humanoid robot balanced automatically during movement of all other limbs. Actually, it offers an ability of whole body coordination to humanoid robot. Third, the posture/walking controller is completed by adding the CoM controller minus the zero moment point controller to the suggested kinematic resolution method. We prove that the proposed posture/walking controller brings the disturbance input-to-state stability for the simplified bipedal walking robot model. Finally, the effectiveness of the suggested posture/walking control method is shown through experiments with regard to the arm dancing and walking of humanoid robot.     

仿人机器人下楼梯的自适应模糊控制方法

针对仿人机器人下楼梯时的稳定行走问题,提出基于虚拟零力矩点的自适应模糊控制方法。按一定约束条件规划各个关节的运动轨迹,利用模糊控制器得到地面反作用力点的位置,根据脚力传感器反馈信息进行适当修正,得到理想关节轨迹。仿真结果证明,该方法具有实时性和有效性。     

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.     

基于自学习中枢模式发生器的仿人机器人适应性行走控制

为了克服传统中枢模式发生器(Central pattern generator, CPG)关节空间控制方法的复杂性和局限性, 本文基于自学习中枢模式发生器模型, 提出了一套在线调制和融合多传感器信息的仿人机器人环境自适应行走控制方法.算法难点在于如何在机器人的工作空间将自学习CPG用于工作空间轨迹生成, 并使CPG参数直接和步态模式相关联.本文提出了利用自学习CPG来学习和实时生成机器人质心轨迹和脚掌轨迹的方法, 在线调节机器人步长、抬腿高度和步行速度等关键参数.参考生物反射行为, 利用传感反馈信息激发CPG以产生具有环境适应性的工作空间轨迹, 提升行走质量. 控制系统的参数通过优化算法来进一步改善行走性能.相比于传统的CPG关节空间法, 本文所采用的自学习CPG工作空间法不仅极大简化了CPG网络结构而且提高了仿人机器人行走的适应性.最后, 通过仿人机器人坡面适应性行走的仿真和实验, 验证了所提出控制策略的可行性和有效性.     

Adjustment of Home Posture of Biped Humanoid Robot Using Sensory Feedback Control

Humanoid robot dynamic walking is seriously affected by the initial home posture (walking ready posture). If the initial home posture is not accurate, the robot may fall down during walking despite using robust walking control algorithm. Moreover, the initial home posture of a real physical robot is slightly different at every setting because the zero position of the joint is not exactly the same. Therefore, an accurate and consistent initial home posture is essential when we compare and analyze walking control algorithms. In order to find a zero position, an incremental encoder with a limit switch or an absolute encoder such as a potentiometer can generally be used. However, the initial calibration of this method for a multi-axis humanoid robot that enables the desired initial sensor signal is difficult and time-consuming. Furthermore, it has the disadvantage that additional limit switches or absolute encoders can interfere with the design objective of compactness. Therefore, this paper describes a novel adjustment method of the home posture for a biped humanoid robot utilizing incremental encoders, an inertial sensor and force torque sensors. Four kinds of controllers are proposed for the adjustment of the home posture and adjusted offsets are measured when the outputs of the controllers have converged. Experimental results from KHR-2 show the effectiveness of the proposed adjustment algorithm.     

Compliance control for stabilizing the humanoid on the changing slope based on terrain inclination estimation

This paper presents a stabilization framework integrated with the estimation of the terrain inclination to balance a humanoid on the changing slope as an extension to our previous study. In this paper, the estimation of the terrain inclination is improved for walking in place on an inclination-varying slope. A passivity based admittance control utilizes the force/torque sensing in feet to actively regulate the impedance at the center of mass to stabilize the robot. The logic-based inclination estimation algorithm uses the feet to probe the terrain and deals with the under-actuation. The equilibrium set-point in the admittance control is regulated based on the detected inclination. The effectiveness of the control framework is validated on the humanoid robot COMAN and demonstrated by estimating the terrain inclination, coping with the under-actuation phase, adapting to the slope with changing inclination during both standing and walking. Experimental data are analyzed and discussed, and the future work is suggested.     

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.     

基于时域无源性控制的六足机器人双边触觉遥操作

随着六足机器人研究工作的深入,针对其遥操作系统的开发面临诸多挑战.为了弥补松软接触条件对系统可控性及稳定性的影响,提出一种基于时域无源性控制(time-domain passivity control,TDPC)的六足机器人双边触觉遥操作方法.其主从两端采取位置-速度的交互模式,通过分析足-地柔性接触的作用机理,构建无源观测器和无源控制律以补偿足底滑移所导致环境系统的潜在有源性,采用速度跟踪模式设计基于触觉力反馈的系统控制架构,并利用Llewellyn准则确定控制律参数的稳定范围.最后,搭建半物理仿真实验平台并验证所提出的双边触觉遥操作方法在松软地形条件下能够保证六足机器人遥操作系统的稳定,且兼具较好的持续跟踪能力.     

基于多传感器集成的仿人机器人足部感知系统

足部是仿人机器人本体支撑的基础,也是唯一与地面接触并发生相互作用的主要部件,其各种地面信息获取能力是机器人实现仿人的自然性稳定行走控制的关键.基于六维力传感器、惯量测量单元和柔性触觉阵列传感器,设计了一种新型仿人机器人集成化足部感知系统(IPFS).具备对各种地面环境识别和足部姿态获取、足底与外界接触位置的实时感知和估...     

ADXL203型双轴加速计在机器人足部感知系统中的应用

仿人机器人要实现在复杂环境下稳定行走,仅仅依靠地面反力信息远不能满足应用要求,此时足部的倾角信息显得更为重要。脚面倾角可以反映地面倾斜状态,是仿人机器人稳定控制的一个重要依据。利用ADXL203双轴加速度传感器与DSP(TMS3202811)实现对倾角信息的实时高速采集与处理,并通过实验证明了倾角传感器在机器人足部感知系统中是可行的。     

Full-Body Compliant Human–Humanoid Interaction: Balancing in the Presence of Unknown External Forces

This paper proposes an effective framework of human-humanoid robot physical interaction. Its key component is a new control technique for full-body balancing in the presence of external forces, which is presented and then validated empirically. We have adopted an integrated system approach to develop humanoid robots. Herein, we describe the importance of replicating human-like capabilities and responses during human-robot interaction in this context. Our balancing controller provides gravity compensation, making the robot passive and thereby facilitating safe physical interactions. The method operates by setting an appropriate ground reaction force and transforming these forces into full-body joint torques. It handles an arbitrary number of force interaction points on the robot. It does not require force measurement at interested contact points. It requires neither inverse kinematics nor inverse dynamics. It can adapt to uneven ground surfaces. It operates as a force control process, and can therefore, accommodate simultaneous control processes using force-, velocity-, or position-based control. Forces are distributed over supporting contact points in an optimal manner. Joint redundancy is resolved by damping injection in the context of passivity. We present various force interaction experiments using our full-sized bipedal humanoid platform, including compliant balance, even when affected by unknown external forces, which demonstrates the effectiveness of the method.     

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.     

Realization of Dynamic Stair Climbing for Biped Humanoid Robot Using Force/Torque Sensors

This paper proposes a control algorithm for the dynamic stair climbing of a human-sized biped humanoid robot. Dynamic stair climbing can cause more instability than dynamic biped walking on the ground because stair climbing requires an additional vertical motions and a large step length. We assume that stair configuration is already known and only use force/torque sensors at ankle joint to achieve a control algorithm for a stable dynamic stair climbing. We describe a stair climbing pattern generation and stair climbing stages, and then propose a real-time balance control algorithm which is composed of several online controllers. Each online controller is addressed in detail with experimental results. Finally, the effectiveness and performance of the proposed control algorithm are verified through a dynamic stair climbing experiment of KHR-2.     

小型仿人机器人控制系统设计

本文提出了一种以ARM9为主控制器的新型的仿人机器人分布式控制系统。单片机和外部计数器组成关节控制器。主控制器和关节控制器之间采用USB通信。从而实现了控制系统的小型化和低功耗。通过该系统控制小型仿人机器人完成了行走实验。     

A desired landing points walking method enablinga planner quadruped robot to walk on rough terrain

It is necessary for legged robots to walk stably and smoothly on rough terrain.In this paper,a desired landing points(DLP) walking method based on preview control was proposed in which an off-line foot motion trace and an on-line modification of the trace were used to enable the robot to walk on rough terrain.The on-line modification was composed of speed modification,foot lifting-off height modification,step length modification,and identification and avoidance of unsuitable landing terrain.A planner quadruped robot simulator was used to apply the DLP walking method.The correctness of the method was proven by a series of simulations using the Adams and Simulink.     

Error Analysis and Effective Adjustment of the Walking-Ready Posture for a Biped Humanoid Robot

A walking control algorithm is generally a mixture of various controllers; it depends on the characteristics of the target system. Simply adopting one part of another researcher's algorithm does not guarantee an improvement in walking performance. However, this paper proposes an effective algorithm that can be easily adopted to other biped humanoid robots; the algorithm enhances the walking performance and stability of the robot merely by adjusting the walking-ready posture. The walking performance of biped humanoid robots is easily affected by an unsuitable walking-ready posture in terms of accuracy and repeatability. More specifically, low accuracy for the walking-ready posture may cause a large difference between an actual biped robot and its mathematical model, and the low repeatability may disturb the evaluation of the performances of balance controllers. Therefore, this paper first discusses the factors that detrimentally affect bipedal walking performance and their phenomena in the walking-ready posture. The necessary conditions for an ideal walking-ready posture are then defined based on static equilibrium and a suitable adjustment algorithm is proposed. Finally, the effectiveness of the algorithm is verified through dynamic computer simulations.