双足机器人自适应常值驱动与传感反馈结合的仿生行走控制

为了将双足机器人的混沌步态控制收敛到稳定的周期步态,提出一种控制策略。首先用庞卡莱截面法研究斜坡倾角变化对步态的影响,结果表明,坡度增大会导致倍周期步态到混沌步态的产生;然后以人类步行的生物力学为仿生依据,根据延迟反馈控制的基本思路,设计了自适应常值驱动与传感反馈相结合的仿生行走控制策略,并依据当前步和前两步初始状态对控制器参数进行逐步调节,最终将混沌步态控制收敛到周期步态。仿真结果表明了所提出算法的有效性。     

双足机器人动态行走时踝关节的力矩控制问题

本文从实现单-双脚支撑期的平滑过渡及减小前脚着地冲击的角度出发,分析了双足机器人动步态时踝关节的控制对连续、平滑行走带来的影响.指出为实现平滑过渡及减小冲击在踝关节上不宜采用高增益位置反馈控制,而应采用力矩反馈控制.本文给出了力矩反馈控制的实现方法.该方法无需复杂的软件、硬件支持,能满足实时控制的要求.采用本文的方法实现了 HIT-13双足机器人稳定的动态行.     

基于主—从控制的双足机器人动步态行走

本文给出一种基于主-从控制实现双足机器人动步态行走的控制方法.该方法计算量小,可以在线规划步态及实现双脚支撑期平滑的动态切换.仿真及实验结果验证了方法的有效性及可行性,实现了变步态动态行走.实验所采用的装置为 HLTR—13双足机器人.该机器人重65kg,高1.1m,具有12个自由度.实验结果表明,本文给出的方法能较好地实现变步态动态行走。从而使机器人具有较强的环境适应能力.     

一种基于神经网络感知器的双足行走机器人稳定性控制方法

本文利用神经网络感知器和安装在机器人脚底的力传感器，测知机器人重心的位置，控制机器人重心在双脚的支撑面内，以使机器人稳定。本文提出的双足行走机器人稳定性控制方案是简单易行的。     

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.     

复杂路况下双足机器人稳定行走的设计与研究

以ATMEL公司的Atmega128为核心设计控制、驱动电路来实现双足机器人在复杂路况下的稳定行走。ATmega128内部16位定时器及I/O端口产生多路PWM输出控制舵机,同时Atmega128作为主控制器,利用传感器ADXL345传回的角速度变化辅以机器人脚部的触碰开关来实时调整机器人的姿态,以使机器人在不平坦路面上稳定行走。     

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.     

仿生双足机器人步态轨迹自适应控制方法研究

仿生双足机器人的步态控制具有高阶、高耦合,以及不完整约束等复杂特征,为了使其行走性能更接近人体,基于模型分析提出了一种步态轨迹自适应控制方法.首先在人体步态变化对质心投影位置与质心角动量影响的基础上,引入倒立摆建立步态模型来模拟人体行走状态,同时推导出质心投影点位置与速度公式.然后为了实现步态轨迹自适应控制,对影响步态...     

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。     

Robust Sliding-mode Control of Nine-link Biped Robot Walking

A nine-link planar biped robot model is considered which, in addition tothe main links (i.e., legs, thighs and trunk), includes a two-segment foot.First, a continuous walking pattern of the biped on a flat terrain issynthesized, and the corresponding desired trajectories of the robot jointsare calculated. Next, the kinematic and dynamic equations that describe itslocomotion during the various walking phases are briefly presented. Finally,a nonlinear robust control approach is followed, motivated by the fact thatthe control which has to guarantee the stability of the biped robot musttake into account its exact nonlinear dynamics. However, an accurate modelof the biped robot is not available in practice, due to the existence ofuncertainties of various kinds such as unmodeled dynamics and parameterinaccuracies. Therefore, under the assumption that the estimation error onthe unknown (probably time-varying) parameters is bounded by a givenfunction, a sliding-mode controller is applied, which provides a successfulway to preserve stability and achieve good performance, despite the presenceof strong modeling imprecisions or uncertainties. The paper includes a setof representative simulation results that demonstrate the very good behaviorof the sliding-mode robust biped controller.     

Locomotion Control of a Biped Robot Using Nonlinear Oscillators

Recently, many experiments and analyses with biped robots have been carried out. Steady walking of a biped robot implies a stable limit cycle in the state space of the robot. In the design of a locomotion control system, there are primarily three problems associated with achieving such a stable limit cycle: the design of the motion of each limb, interlimb coordination, and posture control. In addition to these problems, when environmental conditions change or disturbances are added to the robot, there is the added problem of obtaining robust walking against them. In this paper we attempt to solve these problems and propose a locomotion control system for a biped robot to achieve robust walking by the robot using nonlinear oscillators, each of which has a stable limit cycle. The nominal trajectories of each limb's joints are designed by the phases of the oscillators, and the interlimb coordination is designed by the phase relation between the oscillators. The phases of the oscillators are reset and the nominal trajectories are modified using sensory feedbacks that depend on the posture and motion of the robot to achieve stable and robust walking. We verify the effectiveness of the proposed locomotion control system, analyzing the dynamic properties of the walking motion by numerical simulations and hardware experiments. Shinya Aoi received the B.E. and M.E. degrees from the Department of Aeronautics and Astronautics, Kyoto University, Kyoto, Japan in 2001 and 2003, respectively. He is a Ph.D. candidate in the Department of Aeronautics and Astronautics, Kyoto University. Since 2003, he has been a research fellow of the Japan Society for the Promotion of Science (JSPS). His research interests include dynamics and control of robotic systems, especially legged robots. He is a member of IEEE, SICE, and RSJ. Kazuo Tsuchiya received the B.S., M.S., and Ph.D. degrees in engineering from Kyoto University, Kyoto, Japan in 1966, 1968, and 1975, respectively. From 1968 to 1990, he was a research member of Central Research Laboratory in Mitsubishi Electric Corporation, Amagasaki, Japan. From 1990 to 1995, he was a professor at the Department of Computer Controlled Machinery, Osaka University, Osaka, Japan. Since 1995, he has been a professor at the Department of Aeronautics and Astronautics, Kyoto University. His fields of research include dynamic analysis, guidance, and control of space vehicles, and nonlinear system theory for distributed autonomous systems. He is currently the principal investigator of “Research and Education on Complex Functional Mechanical Systems” under the 21st Century Center of Excellence Program (COE program of the Ministry of Education, Culture, Sports, Science and Technology, Japan).     

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。     

Control of a Biped Walking Robot during the Double Support Phase

This paper discusses the control problem of a biped walking robotduring the double-support phase. Motion of a biped robot during thedouble-support phase can be formulated as motion of robotmanipulators under holonomic constraints. Based on the formulation,the walking gait is generated by controlling the position of thetrunk of the robot to track a desired trajectory, referenced in theworld frame. Constrained forces at both feet were controlled suchthat firm contact is preserved between the feet and ground by using asimplified model of the double-support phase. The control scheme wasevaluated experimentally.     

双足机器人稳定步行模式预测控制实现方法的研究

针对现有的预测控制生成步行模式方法中忽略了参数间关系和参数取值范围的问题进行探讨.预测控制通过控制质心运动生成步行模式以实现ZMP目标轨迹跟踪,根据预测控制器模型研究参数间的关系,并通过极点分析讨论其取值范围,提出关键参数在容许取值范围内,可以保证系统的稳定性,并生成满足稳定步行的质心运动.通过仿真实验分析了在存在扰动情况下,关键参数取适当值,能够生成稳定的步行模式.     

双足步行机器人的ZMP-CoP检测及研究

ZMP(零力矩点）和CoP(压力中心)是评价双足步行机构行走稳定性的重要参数．本文在研究了ZMP和CoP两者关系的基础上,根据THBIP-I仿人机器人基于ZMP理论的姿态调整要求和六维力/力矩传感器的安装位置,推导了适用于双足机器人的CoP计算公式,建立了采用六维力/力矩传感器的CoP检测系统．进行了THBIP-I仿人机器人行走过程的实际CoP检测实验,并对实验结果进行了讨论．实验证明了该系统的准确性.     

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.     

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.     

动态步行双足机器人THR-I的设计与实现

为了既能验证动态步行的理论结果,又能满足经济性的要求,本文设计并实现了一种基于总线型伺服电机的平面无脚双足机器人THR-I．首先介绍了该机器人的系统构成,包括机械结构部分和控制系统部分;在建立步行动力学方程时,考虑了中心约束系统的耦合影响．然后,利用虚拟约束原理,设计了步行约束,并成功实现了步行周期为0     

双足机器人步态控制研究方法综述

概括地介绍了双足机器人步态控制领域内的主要研究思路．详细阐述了基于双足动力学特征的3种建模方法,包括倒立摆模型、被动步态模型、质量弹簧模型的特点．另外讨论了两种常用的约束条件(稳定判据与能量约束)和3种智能控制方法(神经元理论、模糊逻辑与遗传算法)在双足机器人步态控制中的研究情况．