变刚度半被动双足机器人行走的仿人控制1)

研究了变刚度半被动双足机器人行走控制问题。采用仿人的行走控制策略,使用变刚度双足弹簧负载倒立摆模型,利用模型自稳定性,在双支撑阶段调整后腿刚度使机器人的能量保持在期望能量附近,在单支撑阶段调整摆动腿落地位置控制质点的高度和前向速度。仿真结果表明：本文采用的控制策略可以实现双足机器人在水平面上的稳定行走,无扰动时可以使机器人实现零输入的被动周期行走,有外部扰动时腿部变刚度控制可使机器人总能量恢复平衡并重新进入稳态行走,控制系统具有鲁棒性。     

考虑摆动腿动态的变长度柔性双足机器人步态切换控制研究

弹簧负载倒立摆模型是一种典型的双足行走模型,已经成为研究机器人类人行走的基础。本文在此模型的基础上进行了扩展,通过添加刚性躯干、脚质量及采用变长度伸缩腿,充分考虑了躯干及摆动腿动力学对机器人行走步态的影响。首先,利用欧拉–拉格朗日法推导了动力学方程。其次,设计了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。第三,提出了步态切换策略,通过控制腿部长度和髋关节力矩来实现步态切换,从而改变平均行走速度。最后,通过计算机仿真验证了该方法的有效性。仿真结果表明：该控制策略能够有效地跟踪系统的期望轨迹及实现两种自然步态之间的切换,并形成稳定的极限环,实现机器人的稳定行走。

     

变长度弹性伸缩腿双足机器人动力学与控制

研究了半被动双足机器人的平面稳定行走的控制问题．基于弹簧质点模型，采用拉格朗日方法分别得到双足机器人单支撑阶段与双支撑阶段的动力学方程，对机器人系统的动力学方程求得周期解．应用非线性系统状态反馈线性化理论，在双足机器人的单支撑阶段和双支撑阶段中，通过控制双足机器人的腿长度，实现稳定的周期行走．在理论分析的基础上，对控制算法进行了仿真与研究．结果表明：在周期行走过程中，文中采用的变长度控制算法可以使双足机器人克服外界的干扰，并具有较强的抗干扰性．     

Modeling and analysis of passive dynamic bipedal walking with segmented feet and compliant joints

Passive dynamic walking has been developed as a possible explanation for the efficiency of the human gait. This paper presents a passive dynamic walking model with segmented feet, which makes the bipedal walking gait more close to natural human-like gait. The proposed model extends the simplest walking model with the addition of flat feet and torsional spring based compliance on ankle joints and toe joints, to achieve stable walking on a slope driven by gravity. The push-off phase includes foot rotations around the toe joint and around the toe tip, which shows a great resemblance to human normal walking. This paper investigates the effects of the segmented foot structure on bipedal walking in simulations. The model achieves satisfactory walking results on even or uneven slopes.     

Input torque sensitivity to uncertain parameters in biped robot

Input torque is the main power to maintain bipedal walking of robot, and can be calculated from trajectory planning and dynamic modeling on biped robot. During bipedal walking, the input torque is usually required to be adjusted due to some uncertain parameters arising from objective or subjective factors in the dynamical model to maintain the pre-planned stable trajectory. Here, a planar 5-link biped robot is used as an illustrating example to investigate the effects of uncertain parameters on the input torques. Kine-matic equations of the biped robot are firstly established by the third-order spline curves based on the trajectory planning method, and the dynamic modeling is accomplished by taking both the certain and uncertain parameters into account. Next, several evaluation indices on input torques are intro-duced to perform sensitivity analysis of the input torque with respect to the uncertain parameters. Finally, based on the Monte Carlo simulation, the values of evaluation indices on input torques are presented, from which all the robot param-eters are classified into three categories, i.e., strongly sensi-tive, sensitive and almost insensitive parameters.     

ZMP based neural network inspired humanoid robot control

This paper concerns ZMP-based control that is inspired by artificial neural networks for humanoid robot walking on varying sloped surfaces. Humanoid robots are currently one of the most exciting research topics in the field of robotics, and maintaining stability while they are standing, walking or moving is a key concern. To ensure a steady and smooth walking gait of such robots, a feedforward type of neural network architecture, trained by the back-propagation algorithm, is employed. The inputs and outputs of the neural network architecture are the ZMPx and ZMPy errors of the robot, and the x, y positions of the robot, respectively. The neural network developed allows the controller to generate the desired balance of the robot positions, resulting in a steady gait for the robot as it moves around on a flat floor, and when it is descending or ascending slopes. In this paper, experiments of humanoid robot walking are carried out, in which the actual position data from a prototype robot are measured in real-time situations, and fed into a neural network inspired controller designed for stable bipedal walking. In addition, natural walking motions on the different surfaces with varying slopes are obtained and the performance of the resulting controller is shown to be satisfactory.     

Treadmill walking of the pneumatic biped Lucy: Walking at different speeds and step-lengths

Actuators with adaptable compliance are gaining interest in the field of legged robotics due to their capability to store motion energy and to exploit the natural dynamics of the system to reduce energy consumption while walking and running. To perform research on compliant actuators we have built the planar biped Lucy. The robot has six actuated joints, the ankle, knee and hip of both legs with each joint powered by two pleated pneumatic artificial muscles in an antagonistic setup. This makes it possible to control both the torque and the stiffness of the joint. Such compliant actuators are used in passive walkers to overcome friction when walking over level ground and to improve stability. Typically, this kind of robots is only designed to walk with a constant walking speed and step-length, determined by the mechanical design of the mechanism and the properties of the ground. In this paper, we show that by an appropriate control, the robot Lucy is able to walk at different speeds and step-lengths and that adding and releasing weights does not affect the stability of the robot. To perform these experiments, an automated treadmill was built Published in Prikladnaya Mekhanika, Vol. 44, No. 7, pp. 134–142, July 2008.     

Efficient parametric excitation walking with delayed feedback control

In passive dynamic walking proposed by McGeer, mechanical energy lost by heel strike is restored by transporting potential energy to kinetic energy as walking down a slope. When energy input is larger as a slope is steeper, the bifurcation of a walking cycle occurs. In the parametric excitation walking, which is to realize passive dynamic-like walking on the level ground, the bifurcation of a walking cycle has also been observed when walking speed is fast. Recently, Asano et al. have shown that bifurcation exerts an adverse influence upon walking performance by using a rimless wheel model. In this paper, we apply the delayed feedback control (DFC), originally used in chaos control, to parametric excitation walking to suppress bifurcation. We show in numerical simulation that the proposed method makes period-two walking to period-one walking, and improves energy efficiency. In addition, the proposed method can generate a sustainable gait in the region where a biped robot cannot walk without DFC. The analyses using a Poincaré map reveal that period-one walking with DFC corresponds to an unstable periodic orbit and reveal that a robot model in this paper satisfies the sufficient condition of applicability of DFC.     

漂浮基双臂空间机器人姿态与末端抓手惯性空间轨迹协调运动的模糊滑模控制

本文讨论了载体姿态受控、位置不受控制的双臂空间机器人系统的控制问题.利用拉格朗日方法并结合系统动量守恒关系,建立了双臂空间机器人系统的非线性系统动力学模型.以此为基础,考虑到空间机器人系统结构的复杂性及其某些参数的变动性,根据具有较强鲁棒性的变结构控制理论,设计了双臂空间机器人载体姿态与两机械臂末端抓手惯性空间轨迹协调运动的滑模变结构控制方案.为了克服滑模变结构控制器抖振的缺点,附加设计了一个模糊控制器,以便根据系统的输出来动态调节滑模变结构控制器等速趋近率的系数,从而既确保了系统的快速响应而又消除了原有的抖振.系统数值仿真,证明了上述控制方案良好的控制效果.     

Disturbance compensation of a dual-arm underwater robot via redundant parallel mechanism theory

Disturbance compensation is one of the major issues for underwater robots to hover as a mobile platform and to manipulate an object in an underwater environment. This paper presents a new strategy of disturbance compensation for a mobile dual-arm underwater robot using internal torques derived from redundant parallel mechanism theory. A model of the robot was analyzed by redundant serial and parallel mechanisms at the same time. The joint torque to operate the robot is obtained from a redundant serial mechanism model with null-space projection due to redundancy. The joint torque derived from the redundant parallel kinematic model is calculated to perfectly compensate for disturbances to the mobile platform and is included in the solution of the joint torque based on the serial redundant model. The resultant joint torque can generate force on the end-effector for required tasks and forces for disturbance compensation simultaneously . A simulation shows the performance of this disturbance compensation strategy. The joint torque based on the algorithm generates the desired task force and the disturbance compensation force together, and a little additional joint torque can generate a large internal force effectively due to the characteristics of a redundant parallel mechanism. The proposed method is more effective than compensation methods using thrusting force on the mobile platform.     

一种压电驱动的三足爬行机器人

机器人领域涉及到力学、机械、材料、控制、电子和计算机等多个学科. 其中, 爬行机器人可在极端环境下工作, 进而可有效降低人工作业的危险性并提高工作效率. 因此, 爬行机器人一直是机器人领域的重点研究对象. 压电陶瓷是一种能够将机械能和电能互相转换的新型功能陶瓷材料. 逆压电效应是指当在电介质的极化方向施加电场, 这些电介质就在一定方向上产生机械变形或机械压力, 当外加电场撤去时, 这些变形或应力也随之消失. 本文基于压电陶瓷的逆压电效应设计了一种由3条弯曲变截面梁支撑的一体化三足爬行机器人. 利用理论力学方法对该三足爬行机器人建立整体受力分析方程, 再用哈密顿原理对变截面、变角度梁建立动力学方程, 最终得到了可求解该三足爬行机器人的压电驱动腿固有频率的方程. 设计并制作了三足爬行机器人实物, 通过实验测试了不同弯折角度、不同驱动频率、不同负载、不同电压波形对运动方向及运动速度的影响. 最后利用不对称的驱动电压使三足爬行机器人实现了左转、右转以及不加导轨的近似直线运动, 实现了设计的3个方向的运动, 最后分析了该机器人的能耗问题. 该研究可为微型爬行机器人设计和实验提供参考依据.      

A proposed hybrid neural network for position control of a walking robot

The use of a proposed recurrent neural network control system to control a four-legged walking robot is presented in this paper. The control system consists of a neural controller, a standard PD controller, and the walking robot. The robot is a planar four-legged walking robot. The proposed Neural Network (NN) is employed as an inverse controller of the robot. The NN has three layers, which are input, hybrid hidden and output layers. In addition to feedforward connections from the input layer to the hidden layer and from the hidden layer to the output layer, there is also a feedback connection from the output layer to the hidden layer and from the hidden layer to itself. The reason to use a hybrid layer is that the robot’s dynamics consists of linear and nonlinear parts. The results show that the neural-network controller can efficiently control the prescribed positions of the stance and swing legs during the double stance phase of the gait cycle after sufficient training periods. The goal of the use of this proposed neural network is to increase the robustness of the control of the dynamic walking gait of this robot in the case of external disturbances. Also, the PD controller alone and Computed Torque Method (CTM) control system are used to control the walking robot’s position for comparison.     

Detumbling strategy and coordination control of kinematically redundant space robot after capturing a tumbling target

This paper focuses on the motion planning to detumble and control of a space robot to capture a non-cooperative target satellite. The objective is to construct a detumbling strategy for the target and a coordination control scheme for the space robotic system in post-capture phase. First, the dynamics of the kinematically redundant space robot after grasping the target is presented, which lays the foundation for the coordination controller design. Subsequently, optimal detumbling strategy for the post-capture phase is proposed based on the quartic B\(\acute{\text{ e }}\)zier curves and adaptive particle swarm optimization algorithm subject to the specific constraints. Both detumbling time and control torques were taken into account for the generation of the optimal detumbling strategy. Furthermore, a coordination control scheme is designed to track the designed reference path while regulating the attitude of the chaser to a desired value. The space robot successfully dumps the initial velocity of the tumbling satellite and controls the base attitude synchronously. Simulation results are presented for detumbling a target with rotational motion using a seven degree-of-freedom redundant space manipulator, which demonstrates the feasibility and effectiveness of the proposed method.     

A Note on a Walking Machine Model

The paper continues studies intended to find out whether it is possible to create a prototype walking machine with relatively simple components. In this connection, the control problem is solved for a two-dimensional model of biped machine. It has a torso and two telescopic legs. Each leg includes a ponderable section of constant length and an imponderable section of variable length. The machine, regarded as a system with variable constraints, implements a single-stance gait (one stance leg at a time) with a step of constant duration. The contact of the swing leg with the ground is analyzed within the framework of Carnot's theorem (perfectly inelastic impact). It is assumed that the force developed in the stance leg is due to the deformation of the leg's spring and that this deformation can be controlled. An algorithm is proposed to synthesize a control system that takes into account collisions occurring at reverse of the roles of the legs. This algorithm is based on methods of optimizing periodic systems. The algorithm is compared with approaches used by other authors     

Shape memory elastic foundation and supports for passive vibration control of composite plates

The paper presents an approach to passive vibration control of shear deformable and thin plates. The first of two methods of vibration control employs prestressed shape memory alloy (SMA) wires embedded in sleeves attached to the surface of the plate. The spacing between the wires can be arbitrary and variable enabling the development of a SMA support system for maximum control with minimum additional weight. The other method considered in the paper utilizes SMA wires supporting the plate at strategically selected points. The mechanism of passive control includes two components: (1) SMA wires prestressed as a result of constrained phase transformation act as an elastic foundation with a variable stiffness and (2) energy dissipation occurs as a result of hysteresis in superelastic wires vibrating together with the structure. As follows from examples, it is possible to achieve a significant reduction of the vibration amplitude over a broad spectrum of driving frequencies using any of two methods considered in the paper.     

Impactless biped walking on a slope

Walking without impacts has been considered in dynamics as a motion/force control problem. In order to avoid impacts, an approach for both the specified motion of the biped and its ground reaction forces was presented yielding a combined motion and force control problem. As an application, a walker on a horizontal plane has been considered. In this paper, it is shown how the control of the ground reaction forces and the energy consumption depend on the gradient of a slope. The biped dynamics and the constraints within the biped system and on the ground are discussed. A motion control synthesis is developed using the inverse dynamics principle proven to be most efficient for human walking research, too. The impactless walking with controlled legs is illustrated by a seven-link biped. The “flying” biped has nine degrees of freedom, with six control inputs. During locomotion, the standing leg has three scleronomic constraints, and the trunk has three rheonomic constraints. However, there are three rheonomic constraints for the prescribed leg motion or three scleronomic constraints for reaction forces of the trailing leg, respectively. The nominal control action for impactless walking can be precomputed and stored. The model proposed allows the investigation of several problems: uphill and downhill walking, optimization of step length, stiction of the feet on the slope and many more. All these findings are also of interest in biomechanics.     

空间双臂机器人抓捕翻滚目标后的鲁棒稳定控制

针对空间双臂机器人抓捕翻滚目标的稳定控制问题,由于目标惯性参数的不确定性以及双臂同时作用于目标存在内力挤压,已有的稳定控制方法无法有效地约束机械臂末端与目标的接触力与力矩,无法保证控制过程中抓捕点处的接触安全.为此,本文考虑被抓捕目标惯性参数不确定性与双臂内力挤压对抓捕后阶段组合体稳定控制的影响,提出了一种保证接触安全...     

基于干扰观测器的柔性关节空间机器人退步自适应控制

研究了载体位置、姿态均不受控的情况下,系统参数不确定的柔性关节空间机器人轨迹跟踪的控制问题.结合系统动量、动量矩守恒关系,利用拉格朗日法推导出系统的动力学模型.为减小系统柔性关节对系统控制精度的影响,采用关节柔性补偿器来等效降低系统关节的柔性.再借助奇异摄动法,针对系统参数不确定的情况,设计了柔性关节空间机器人基于干扰观测器的退步自适应滑模控制方案.该方案不需要对系统惯性参数进行线性化处理,控制器结构简单,且实现了空间机器人期望轨迹的精确跟踪控制.通过平面两杆空间机器人的数值仿真证明了该方法的有效性.     

A robust method on estimation of Lyapunov exponents from?a?noisy time series

Lyapunov exponents can indicate the asymptotic behaviors of nonlinear systems, and thus can be used for stability analysis. However, it is notoriously difficult to estimate these exponents reliably from experimental data due to the measurement error (noise). In this paper, a novel method for estimating Lyapunov exponents from a time series in the presence of additive noise corruption is presented. The method combines the ideas of averaging the noisy data to form new neighbors and of nonlinear mapping to determine neighborhood mapping matrices. Two case studies of balancing control of a bipedal robot and the Lorenz systems are presented to demonstrate the efficacy of the proposed method. The bipedal robot system has two negative Lyapunov exponents while the Lorenz system has one positive, zero, and negative exponents, respectively. It is shown that, as compared with the existing methods, our proposed one is more robust to the ratio of signal to noise, and is particularly effective in estimating negative Lyapunov exponents. We believe that the work can contribute significantly to the stability analysis of nonlinear systems using a noisy time series.     

Foot force distribution of walking machine with consideration of terrain properties

Determination of foot force distribution during walking is important to the simulation and control of the vehicle. This problem was often considered as an indeterminate problem and several optimization methods were proposed. The indeterminancy, which was due to the assumption of rigid bodies, can, however, be removed by incorporating the compliance equations into the equations of equilibrium. Based on such a compliant model, a s stiffness matrix method was developed to determine the foot force distribution. However, due to the complexity of the problem, the compliance of terrain in the stiffness matrix method was considered either negligible or as a linear spring model. In this paper, two realistic terrain models are incorporated into the stiffness matrix method to study the effect of terrain properties on foot force distribution during walking. These two terrain models are the three-parameter solid model and the four-parameter Burgers model. The former is a model of clay terrain while the latter is a model of a paddy field. These models are extended to three dimensions and then combined with the leg compliances to form the stiffness matrix of the system. The simulation results show that the terrain compliance has significant effect on foot force distribution. For example, it is observed that this compliance helps to distribute the foot forces evenly and to minimize the frictional angles.