智能决策改进的四足机器人ZMP爬行步态算法

提出了一种基于反馈控制和贪婪决策的四足机器人爬行步态规划算法。该算法利用机载惯性传感器IMU（Inertial Measurement Unit）来实时计算零力矩点和姿态角,以稳态裕度为指标在支撑平面内实时规划期望零力矩点（Zero Moment Point,ZMP）轨迹,结合非线性反馈控制器实现对机体ZMP点的连续平滑调节,保证机器人在按给定速度矢量进行连续爬行的同时具有抵抗一定外力扰动的能力。步态规划采用动态步态周期,基于机器人结构约束和贪婪决策实现跨腿的自动触发,提高了步态自适应性。最终通过样机行走实验验证了所提算法应用于微型四足机器人中的可行性,机器人实现了在平坦地面上稳定地全向行走和旋转,所提算法同时兼顾了自适应性和稳定裕度。     

拟人机器人在外力干扰下的步态规划

拟人机器人在外力干扰下的步态规划是机器人行走研究中的重要课题。论文首先讨论了虚拟零力矩点与支撑多边形的位置关系,然后提出了一种基于虚拟零力矩点的优化控制策略,最后采用遗传算法对步态进行优化,仿真结果表明能够提高机器人步态规划的实时性。     

基于六维力/力矩传感器和关节力矩的仿人机器人步态补偿算法

为实现仿人机器人的稳定行走，提出一种根据其足底六维力/力矩传感器信息、针对关节力矩的步态补偿算法．利用直流伺服电机的过载能力，来改善仿人机器人关节在大负载扰动下的动态性能．行走实验证明了该算法在离线实施过程中的有效性．     

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。     

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.     

拟人机器人抗干扰行走稳定性分析

通过引入虚拟零力矩点假设,提出了一个多种外界干扰下拟人机器人的整体分析模型,分析了拟人机器人抗干扰行走的稳定性.给出了支撑多边形的计算机表达方法和失稳时旋转边界的确定方法.为了在不同的情况下保持平衡,提出了改变支撑多边形、手的支撑、改变上体重心等3种新的稳定性恢复方法.通过优化从虚拟零力矩点到旋转边界的距离,提出了恢复平衡的优化算法.通过仿真实例验证了所提出方法的正确可行性.     

HfutEngine 3D仿人机器人步态设计与实现

本文针对具体的双足机器人模型,对机器人进行逆运动学的建模,给出零力矩点（ZMP）计算的具体过程,利用零力矩点为运动中机器人的平衡问题提供很好的解决方案：在仿真平台下,在线计算运动中机器人的ZMP点,并通过分析ZMP的变化,评估动作的稳定性。     

RoboCup3D仿真机器人步态优化研究

在RoboCup3D比赛中,拥有一个快速灵活、稳定的步态模式是赢得机器人足球比赛的关键之一。为了获得这样的步态模式,提出一种双足机器人垂直质心高度可变的机器学习训练方法。首先,通过规划双足机器人垂直质心高度的轨迹、利用倒立摆模型和数值化方法控制零力矩点,实现双足机器人的类人行走。然后,采用自适应协方差矩阵进化算法对步态参数优化,为了获得快速稳定的步行,采用累积分层的学习方法在之前优化的基础上进一步优化。最后,采用蜂拥编队壁障算法验证多机器人环境下优化步态的稳定性、灵活性。实验和竞赛结果均表明本文提出算法的有效性。     

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。     

本期摘要

舵机控制步行机器人系统设计 首先设计了两足步行机器人的本体结构,并选择舵机作为驱动源。然后．基于广义坐标对该机器人进行了运动学建模,该方法运算简便直观易懂。重点讨论了动态步行的算法设计,详细分析了基于零力矩点的仿人机器人动态步行运动规划方法。结合机器人的几何约束和运动约束．推导机器人参数化步态设计的推导公式,机器人步态的参数化设计大大方便了机器人的运动学和动力学分析。     

双足机器人自然ZMP轨迹生成方法研究

为了实现双足机器人类人行走,提出了一种基于自然ZMP轨迹的双足机器人步行模式生成方法。在单腿支撑相,根据基于三维线性倒立摆模型,在设定从脚跟到脚趾移动的自然ZMP轨迹后,得到质心轨迹方程;在双腿支撑相采用线性摆模型生成质心轨迹方程。同时给出了在统一坐标系中的多步规划质心轨迹方程。在RoboCup 3D仿真平台实现了采用自然ZMP轨迹的双足机器人类人稳定步行,实验和竞赛结果都验证了该方法的有效性。     

A walking pattern generation method of humanoid robot MAHRU-R

This paper proposes an omni-directional walking pattern generation method for a humanoid robot MAHRU-R. To walk stably without falling down, a humanoid robot needs the walking pattern. Our previous walking pattern method generated the walking pattern with linear polynomials of the zero moment point (ZMP). It implemented the simple walking like forward/backward walking, side step walking and turning. However, this method was not sufficient to satisfy the various walking which is combined by forward/backward walking, side step walking and turning. We needed to upgrade the walking pattern generation method to implement an omni-directional walking. We use the linear inverted pendulum model consisted of ZMP and center of mass in order to simplify the computation of walking pattern. The proposed method assumes that the state of the following stride is same to the state of the current stride. Using this assumption of walking pattern, the proposed method generates the stable walking pattern for various walking. And the proposed scheme generates the ZMP trajectory with the quartic polynomials in order to reduce the fluctuation of ZMP trajectory by various walking. To implement the efficient walking pattern, this method proposes three walking modules: periodic step module, transient step module and steady step module. Each step module utilizes weighted least square method with future ZMP position information. The effectiveness of the proposed method is verified by simulations of various walking. And the proposed method is confirmed by the experiment of real humanoid robot MAHRU-R.     

基于测力平台阵列的双足步行机器人实际零力矩点检测

提出一种多维力测力平台阵列系统,通过机器人行走过程中脚部与平台接触力的测量,并根据. vukobratovic关于ZMP的定义,得到机器人行走过程的ZMP实际轨迹信息,为双足步行机器人的稳态行走步态规划提 供参考依据.更进一步,该系统也可以用作双足步行机器人行走过程步态规划的实验平台.     

基于CAN 总线的机器人脚力传感器的设计及其应用􀀂

ZMP控制理论已广泛应用于双足步行机器人的步态规划中,行走过程中的实际ZMP轨迹,是通过安装在脚部的两个多维脚力传感器获取的力/力矩信息计算得到.文章提出并设计了一种基于CAN总线接口的双足步行机器人集成化脚力传感器,给出了其硬件组成及软件设计,并详细论述了双足步行机器人行走过程中实际ZMP轨迹的计算方法.     

双足机器人预观控制的ZMP补偿步行模式研究

针对双足机器人的稳定行走,提出了一种预观控制的零力距点（ZMP）补偿步行模式在线生成方法。利用实际ZMP与目标ZMP之间的未来误差信息,基于预观控制计算机器人行走过程中质心的补偿量,事先调整质心轨迹来改变步态。最终使实际ZMP更好地跟踪目标值。12自由度的双足机器人动力学仿真验证了所提出方法的有效性,而且机器人能在一定程度不平整地面上实现稳定行走。     

An effective trajectory generation method for bipedal walking

This paper presents the virtual height inverted pendulum mode (VHIPM), which is a simple and effective trajectory generation method for the stable walking of biped robots. VHIPM, which is based on the inverted pendulum mode (IPM), can significantly reduce the zero moment point (ZMP) error by adjusting the height in the inverted pendulum. We show the relationship between VHIPM and other popular trajectory generation methods, and compare the ZMP errors in walking when trajectories are generated by various methods including VHIPM. We also investigate the sensitivity of the ZMP error in VHIPM to the step length, walking period and mass distribution of a robot. The simulation results show that VHIPM significantly reduces the ZMP errors compared to other methods under various circumstances.     

A Smooth and Efficient Gait Planning for Humanoids Based on Human ZMP

Based on the ZMP(zero moment point)trajectory and the walking data of human,a new method is proposed to improve the robot walking smoothness as well as to save energy.Firstly,a measurement system is designed to measure the data of humans including the ZMP trajectory and the waist trajectory.Secondly,a new gait planning method which includes presetting the allowable ZMP region is proposed through analyzing human data.Thirdly,the new planning method is applied to the multi-link model based gait planning method.Finally,the feasibility of the proposed method is verified by simulation and experiments.     

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。     

A novel compound biped locomotion algorithm for humanoid robots to realize biped walking

In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point （ZMP）. This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity （COG） of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot＇s collapse. Finally, the algorithm is validated by different kinds of simulation experiments.     

Gait Pattern Adaptation for an Active Lower-Limb Orthosis Based on Neural Networks

This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis–patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis–patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle–foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern.