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ADAMS的双足机器人拟人行走动态仿真

在双足机器人HEUBR_1的设计中,下肢采用了一种新的串并混联的仿人结构,并在足部增加了足趾关节.为验证该仿人结构设计的合理性及拟人步态规划的可行性,在ADAMS虚拟环境中建立了双足机器人HEUSR_1的仿真模型.通过拟人步态规划生成了运动仿真数据,在ADAMS虚拟环境中实现了具有足趾运动的拟人稳定行走,经仿真分析,获得了双足机器人HEUBR_1拟人行走步态下的运动学和动力学特性,仿真结果表明:双足机器人HEUBR_1的串并混联的仿人结构设计能够满足行走要求,且拟人步态规划方法可行,有足趾运动的拟人行走具有运动平稳、能耗低、足底冲击力小的特点.稳定行走的仿真步态数据可为下一步双足机器人HEUBR_1样机行走实验提供参考数据.     

基于关键帧相似性的仿人机器人步态规划

为解决传统步态规划方法运算量大、运行时间长的问题,提出一种基于关键帧相似性的仿人机器人步态规划方法,通过对步态关键帧的相似性度量、髋关节的规划、零力矩点(ZMP)的实时校正,实现仿人机器人曲线行走步态的在线调整,调整后的步态能够较好地逼近实际ZMP曲线。实践结果表明,该方法在降低运算量的同时较好解决了仿人机器人的步态稳定及快速规划问题,并且可以减少步态选择不理想时的时间消耗。     

基于三维线性倒立摆的仿人机器人步态规划

为了实时调整仿人机器人的步态,提出一种仿人机器人的步态生成方法。把机器人运动简化为三维线性倒立摆运动模式,通过预先规划好的零力矩点(ZMP)轨迹,根据质心(CoM)和ZMP的关系,求出CoM轨迹;再将前向步态和侧向步态简化为七连杆结构和五连杆结构,利用三角定理求出各个关节的角度,结合ZMP方程讨论了行走过程中的稳定性。利用给定的条件进行了系统的仿真,并结合实际系统及其运行状况进行分析,验证了所提出规划方法的有效性。     

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.     

基于实时意图识别的外骨骼机器人步态切换

根据外骨骼穿戴者的实时运动意图,切换外骨骼机器人的行走步态,是外骨骼机器人研究热点问题之一.针对外骨骼机器人能够根据穿戴者的运动意图控制步态切换问题,提出采集人体表面肌电信号进行解码,通过BP神经网络识别穿戴者的运动意图,实现外骨骼进行步态规划,利用关节角度与足底压力的相关性以及重心轨迹,对所规划的步态的稳定性进行分析,依据不同的运动意图完成步态进行实时切换,验证了基于实时意图识别控制的外骨骼步态切换的可行性.     

基于体感的仿人机器人步态学习与控制

针对现有理想化步态动力学模型规划方法复杂、人为指定参数过多、计算量大的问题,提出一种基于体感数据学习人体步态的仿人机器人步态生成方法。首先,用体感设备收集人体骨骼信息,基于最小二乘拟合方法建立人体关节局部坐标系;其次,搭建人体与机器人映射的运动学模型,根据两者间主要关节映射关系,生成机器人关节转角轨迹,实现机器人对人类行走姿态的学习;然后,基于零力矩点(ZMP)稳定性原则,对机器人脚踝关节转角采用梯度下降算法进行优化控制;最后,在步态稳定性分析上,提出使用安全系数来评价机器人行走稳定程度的方法。实验结果表明,步行过程中安全系数保持在0~0.85,期望为0.4825,ZMP接近于稳定区域中心,机器人实现了仿人姿态的稳定行走,证明了该方法的有效性。     

外骨骼离线参数化上楼梯步态规划

为扩大脊椎损伤患者在外骨骼机器人辅助下的活动范围而不仅仅只是起坐、站立和行走,提出一种离线参数化上楼梯 步态规划算法,该算法基于惯性测量单元检测穿戴者运动意图,基于足底压力传感器计算整个系统的零力矩点（ZMP） 以确 保上楼梯过程的安全性。 该算法根据人体大腿、小腿长度、楼梯高度和宽度等参数规划出关节的最优空间位置轨迹, 然后通 过逆运动学求解关节角度轨迹,该算法可为不同的穿戴者生成适应于不同楼梯尺寸的步态轨迹, 最后 3 名实验者穿戴外骨骼 在楼梯高度 18cm、宽度 26cm 的楼梯上实验,外骨骼按照规划的步态轨迹帮助穿戴者多次完成上楼梯任务,规划的楼梯尺寸 与实际测量的尺寸误差在 2%以内,通过实验验证了该算法的有效性与实用性。     

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。     

移动可伸缩三维倒立摆模型的双足机器人步态控制策略

双足机器人的步态控制策略是保证双足稳定行走的重要条件之一.结合人在行走时ZMP平稳移动的特性,建立了一种移动可伸缩三维倒立摆模型;在约束平面内分析ZMP与COG的运动关系,将ZMP和COG分别定为快变因子和慢变因子,提出了移动可伸缩三维倒立摆模型的双足机器人步态控制策略;最后通过Matlab/ADAMS进行了步态控制仿真研究.仿真结果表明双足机器人可以稳定地行走,验证了该步态控制策略的可行性.     

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 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.     

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.     

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.     

Measurement and comparison of humanoid H7 walking with human being

This paper describes our research efforts aimed at understanding human being walking functions. Using a motion-capture system, force plates and distributed force sensors, walk motion of both human being and humanoid H7 was captured. Experimental results are shown. Comparisons in between human being and H7 walk made using the following characteristics: (1) ZMP trajectories; (2) torso movement; (3) free leg trajectories; (4) joint angle usage; (5) joint torque usage. Furthermore, implications of the comparisons to the humanoid robot are discussed.     

A Fast Dynamically Equilibrated Walking Trajectory Generation Method of Humanoid Robot

This paper describes a fast dynamically equilibrated trajectory generation method for a humanoid robot. From a given input motion and the desired ZMP trajectory, the algorithm generates a dynamically equilibrated trajectory using the relationship between the robot's center of gravity and the ZMP. Three key issues are denoted: 1) an enhanced ZMP constraint which enables the calculation of robot stability even if several limbs are contacting the environment, 2) a simplified robot model is introduced that represents the relationship between its center of gravity and ZMP, 3) a convergence method is adopted to eliminate approximation errors arising from the simplified model. Combining these three key issues together with online ZMP compensation method, humanoid robot H5 have succeeded to walk, step down and so on. Experimental results using humanoid robot H5 are described.     

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.     

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.