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.     

Sensory-based walking motion instruction for biped humanoid robot

This paper describes a sensory-based biped walking motion instruction strategy. Visual and auditory sensors are employed to generate walking patterns according to human orders and to memorize various complete walking patterns effectively and systematically. The motion of lower-limbs for locomotion is created by an online pattern generator based on the sensory information. At the same time, the motion of the trunk and the waist for stability is generated online by a balance control method. Combining these locomotive and balance motions, a complete walking pattern is hierarchically constructed and memorized on a database. The walking instruction is conducted through computer simulation, and its effectiveness is verified.     

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.     

Trajectory generation and control for a biped robot walking upstairs

This paper presents an effective and systematic trajectory generation method, together with a control method for enabling a biped robot to walk upstairs. The COG (center of gravity) trajectory is generated by the VHIPM (virtual height inverted pendulum mode) for the horizontal motion and by a 6th order polynomial for the vertical motion; an ankle compliance control (ACC) is also added into the robot control. The proposed methods are evaluated by simulations as well as being implemented in a robot for the performance verification. The results show that the proposed methods can generate stable motions when walking upstairs, and these can significantly reduce the zero moment point (ZMP) errors compared with other methods, enabling the robot to walk up steeper stairs.     

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.     

3D stable biped walking control and implementation on real robot

A combination of walking control methods was proposed and implemented on a biped robot. The LIPM-based model predictive control (MPC) was adopted to generate a basic stable walking pattern. The stability of pitch and yaw rotation was improved through pitch and yaw momentum control as a supplementation of MPC. It is found that biped robot walking tends to deviate from the planned walking direction if not considering the rotation friction torque in yaw axis under the support foot. There are basically two methods to control yaw momentum, waist and swing arms rotation control. However, the upper body is often needed to accomplish other tasks. Therefore, a yaw momentum control method based on swing leg dynamics was proposed. This idea does not depend on upper body’s motion and is highlighted in this paper. Through experiments, the feasibility of the combination of the control methods proved to be practical in keeping biped robot walking stable both in linear and rotation motion. The pros and cons of the yaw momentum control method were also tested and discussed through comparison experiments, such as walking on flat and uneven terrain, walking with different payloads.     

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。     

The motion control of a statically stable biped robot on an unevenfloor

This work studies the motion control of a statically stable biped robot having seven degrees of freedom. Statically stable walking of the biped robot is realized by maintaining the center-of-gravity inside the convex region of the supporting foot and/or feet during both single-support and double-support phases. The main points of this work are framing the stability in an easy and correct way, the design of a bipedal statically stable walker, and walking on sloping surfaces and stairs.     

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。     

COM motion estimation of a biped robot based on kinodynamics and torque equilibrium

A novel technique to estimate motion of the center of mass (COM) for a biped robot is proposed. A Kalman filter is synthesized where the time evolution of COM is predicted from the external force and corrected based on kinematic estimation and torque equilibrium. They complementarily work to compensate the initial estimation offset, the error accumulation, and errors in modeled mass properties. It makes use of the authors’ previous method to estimate the translational and rotational motion of the base body from inertial information and joint angle measurements. The information about torque equilibrium helps to reduce an uncertainty of the height of COM and to improve the estimation accuracy of it by utilizing an interference of the horizontal and vertical motion of COM. The parameters are tuned based on error analyses in mass properties and sensor signals. A comparative study showed a better performance of the proposed method than other methods through dynamics simulations.     

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.     

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.     

Observer based biped walking control, a sensor fusion approach

In humanoid walking research, the prevailing approach is to utilize an abstraction of the robot to a single center of mass (3D linear inverted pendulum mode). Smaller disturbances or an oscillation of the body are typical for a walking robot and must be addressed by an appropriate sensor feedback. To this end, this paper proposes a novel observer fusing joint angle sensors and force sensing resistors. This new method of sensor feedback in a preview control system balances the walk by damping those disturbances and oscillations of the body. Moreover, novel stabilizing methods for defining reference trajectories for the zero moment point and limbs are examined.     

Stability analysis and time-varying walking control for an under-actuated planar biped robot

This paper presents two walking controllers for a planar biped robot with unactuated point feet. The control is based on the tracking of reference motions expressed as a function of time. First, the reference motions are adapted at each step in order to create a hybrid zero dynamic (HZD) system. Next, the stability of the walking gait under closed-loop control is evaluated with the linearization of the restricted Poincaré map of the HZD. When the controlled outputs are selected to be the actuated coordinates, most periodic walking gaits for this robot are unstable, that is, the eigenvalues of the linearized Poincaré map (ELPM) is larger than one. Therefore, two control strategies are explored to produce stable walking. The first strategy uses an event-based feedback controller to modify the ELPM and the second one is based on the choice of controlled outputs. The stability analysis show that, for the same robot and for the same reference trajectory, the stability of the walking (or ELPM) can be modified by some pertinent choices of controlled outputs. Moreover, by studying some walking characteristics of many stable cases, a necessary condition for stable walking is proposed. It is that the height of swing foot is nearly zero at the desired moment of impact. Based on this condition, the duration of the step is almost constant in presence of initial error, so a method for choosing controlled outputs for the second controller is given. By using this method, two stable domains for the controlled outputs selection are obtained.     

基于CPG的双足机器人多层步行控制器设计

针对双足机器人步行控制器的设计问题,基于生物学启发原理,提出一种基于中枢模式发生器(CPG)与稳定性分析相结合的多层次结构控制器设计方法。分析机器人的步行运动,给出双足运动描述。基于CPG理论设计多层次结构的步行控制器,应用极限环理论方法分析运动稳定性。在保证步行稳定的前提下,所提出的控制方法具有结构简单、通用性好、方便在线平滑修正等优点,步行仿真实验验证了所提出算法的有效性。     

双足机器人步行模式的在线全身修正

提出一种双足机器人步行的在线全身修正方法。根据机器人简化动力学模型规划机器人步行模式。在真实环境中,双足机器人在跟踪预先规划的步行模式时目标值和实际运动状态之间会产生误差。为了减少抑制误差,采用机器人质心补偿,对其全身关节在线修正,以保证行走稳定性。机器人AFU-09的双足步行实验证明了该方法的有效性。     

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。     

无动力双足步行机器人控制策略与算法

本文研究无动力双足步行机器人的建模、分析与控制问题. 基于能量的控制增加了机器人行走极限环的稳定性、鲁棒性, 扩大了极限环的收敛域; 角度不变控制使机器人的稳定行走步态摆脱了地面倾斜角度的限制; 把基于能量的控制与角度不变控制结合起来, 可以实现在不同倾斜角度地面上行走模式的切换. 基于能量的行走平均速度控制方法在平均速度与目标能量之间建立了联系, 能使机器人的行走产生新的稳定步态. 最后, 对无动力双足步行机器人的研究前景做了展望.     

Neuro-fuzzy gait synthesis with reinforcement learning for a biped walking robot

 A reinforcement learning-based neuro-fuzzy gait synthesizer, which is based on the GARIC (Generalized Approximate Reasoning for Intelligent Control) architecture, is proposed for the problem of biped dynamic balance. We modify the GARIC architecture to enable it to generate the trunk trajectory in both sagittal and frontal plane. The proposed gait synthesizer is trained by reinforcement learning that uses a multi-valued scalar signal to evaluate the degrees of failure or success for the biped locomotion by means of the ZMP (Zero Moment Point). It can form the initial dynamic balancing gait from linguistic rules, which are obtained from human intuitive balancing knowledge and biomechanics studies, and accumulate dynamic balancing knowledge through reinforcement learning, and thus constantly improve its gait during walking. The feasibility of the proposed method is verified through a 5-link biped robot simulation.