仿人机器人复杂动态动作设计及相似性研究

提出了一种基于人体运动的考虑节奏相似性的仿人机器人复杂动态动作设计方法. 首先, 把人体的运动分割成基本动作段, 给出了运动学约束, 讨论了复杂动态动作的稳定性调节方法. 然后, 提出了考虑运动节奏的仿人机器人模仿人体动作的相似性函数, 并给出了满足运动学约束和动力学稳定性、具有高相似性的运动轨迹求解方法. 最后, 通过在仿人机器人 BHR-2 上进行中国功夫``刀术'实验验证了该方法的有效性.     

基于运动相似性的仿人机器人双足步行研究

提出了一种基于人体步行运动相似性的仿人机器人双足步行动作设计方法．改进了人体步行轨迹的参 数获取与相似性匹配系统,扩展了相似性函数的适用范围．根据仿人机器人的机械连杆特点定义了步行运动周期中 的关键姿势与子相变换,建立了运动学约束方程,并对行走中出现的动态稳定性问题进行了约束．仿真和实体机器 人实验验证了该方法的有效性．     

基于HMCD的仿人机器人单杠运动控制策略

为完成仿人机器人单杠运动,分析了欠驱动单杠机器人Acrobot模型,并根据IHOG技术要求、实物机器人本体结构和自由度配置,提出了基于HMCD的控制策略.通过单杠视频捕捉获取人体运动数据,根据仿人机器人模型分析关键特征点、基本动作的运动数据得到的关键帧的关节角数据,经过运动学约束调整,采用插值方法生成能够应用于仿人机器人的运动轨迹.在MF-1型仿人机器人单杠实物平台上进行控制实验的成功,验证了该方法的有效性.     

仿人足底肌电特征的机器人行走规划

模仿人类行走规律是规划双足机器人运动的基础.以往模仿人类步态主要通过视觉方法或惯性模块测量(Inertia measurement unit, IMU)方法捕捉人体特征点轨迹.这些方法不考虑零力矩点(Zero moment point, ZMP)的相似性.为解决该问题,本文提出了一种基于足底肌电信号(Electromyography, EMG)和惯性模块测量信号的混合运动规划方法.该方法通过测量足底肌电信号计算出足底压力中心的位置以及踝关节扭矩,结合惯性模块所测量的人体躯干和双足轨迹,来规划双足机器人的步态.首先,用肌电仪测量足底肌电信号,用惯性测量模块测量人体各肢体部分的姿态轨迹,经数据标定后作为仿人机器人的运动参考; 然后,通过预观控制输出稳定的步态.为确保仿人行走的效果,基于人体相似性对运动数据进行了步态优化.实验验证和分析表明, EMG信号超前ZMP约160ms,利用这个特性实现了对压力点位置的有效预测,提高了机器人在线模仿人类行走的稳定性.     

仿人机器人复杂动作设计中人体运动数据提取及分析方法

提出了仿人机器人复杂动作设计中人体运动数据提取及分析方法. 首先, 通过运动捕捉系统获取人体运动数据, 并采用运动重定向技术, 输出人--机简化模型的数据; 然后, 对运动数据进行分析和运动学解算, 给出基于人体运动数据的仿人机器人逆运动学求解方法, 得到仿人机器人模型的关节角数据; 再经过运动学约束和稳定性调节后, 生成能够应用于仿人机器人的运动轨迹. 最终, 通过在仿人机器人BHR-2上进行刀术实验验证了该方法的有效性.     

人体步行规律与仿人机器人步态规划

从仿生学角度分析了人体的步行运动规律,提出了一种基于人体运动规律的仿人机器人步态参数设定方法.首先对人体步行运动数据进行捕捉并分析,得出人体各步态参数间的函数关系,以人体步行相似性作为评价指标,提出仿人机器人步态参数的设定方法.其次,通过分析人体在步行过程中的补偿支撑脚偏航力矩的基本原理,提出了基于双臂及腰关节协调运动的仿人机器人偏航力矩补偿算法,以提高仿人机器人行走的稳定性.最后通过仿真及实验验证了所提出的步态规划方法的正确性及有效性.     

仿人机器人相似性运动研究进展

针对仿人机器人模仿人体运动问题, 从运动轨迹角度比较了基于运动解析方程方法与基于人体运动相似性方法的特点, 阐述了相似性运动系统基本结构, 分析了图像捕捉与处理、相似性特征处理、相似性运动约束与优化等模块功能, 阐述了相似性运动中的人体运动捕获与处理、运动关节解算、运动模型简化与重定向、关键姿势处理与相似度评价、关节空间位姿计算、动力学匹配约束等方面的研究现状, 最后提出了研究展望。     

仿人机器人相似性阶梯行走约束与优化控制

针对基于运动相似性的仿人机器人动作规划中固定运动捕获轨迹难以适应可变目标环境的问题,以仿人机器人上阶梯为例,提出了一种基于运动相似性的行走约束与优化控制方法.首先,为相似性阶梯运动轨迹划分子相关键姿势,施加运动学约束;其次,对运动的稳定性、方向、落脚缓冲等施加动力学约束;再次,结合粒子群优化与分层强化学习方法,提出粒子群分层强化矢量位置择优算法,用于对机器人阶梯运动轨迹进行优化.实验证明了方法的有效性.     

参数化优化的仿人机器人相似性前向倒地研究

提出了一种基于运动相似性的仿人机器人前向倒地动作设计方法.首先,分析了运动相似性并提出了关键姿势同步转换方法; 其次,为机器人前向倒地运动四级倒立摆建立了相似性变换条件下的动力学约束方程与关联的物理条件约束; 再次,引入参数化优化控制与强化技术,对机器人的触地过程进行了参数化优化.实验结果表明了该方法的有效性.     

利用Kinect的人体动作视觉感知算法

提出了一种面向类人机器人的人体动作视觉感知算法,提高了利用Kinect作为视觉输入设备捕捉到的人体动作数据的精度.首先,通过逆运动学方程将捕捉到的关节位移信息转换成角度信息.然后,以角速度和角加速度的变化为依据,将长时间的运动自动分割成独立片段,并用相关向量机原理估计出高精度的角度轨迹.最后,用角度轨迹的空间相似性、时间相似性、平滑度等指标对该算法进行了评估,并在NAO机器人平台上对算法处理后的动作进行了实验验证.实验结果表明,该算法有效提高了动作感知的时空相似性和轨迹平滑度,为高精度的动作模仿奠定了基础.     

Motion planning for humanoid robots based on virtual constraints extracted from recorded human movements

In the field of robotics there is a great interest in developing strategies and algorithms to reproduce human-like behavior. In this paper, we consider motion planning for humanoid robots based on the concept of virtual holonomic constraints. At first, recorded kinematic data of particular human motions are analyzed in order to extract consistent geometric relations among various joint angles defining the instantaneous postures. Second, a simplified human body representation leads to dynamics of an underactuated mechanical system with parameters based on anthropometric data. Motion planning for humanoid robots of similar structure can be carried out by considering solutions of reduced dynamics obtained by imposing the virtual holonomic constraints that are found in human movements. The relevance of such a reduced mathematical model in accordance with the real human motions under study is shown. Since the virtual constraints must be imposed on the robot dynamics by feedback control, the design procedure for a suitable controller is briefly discussed.     

Dynamically-Stable Motion Planning for Humanoid Robots

We present an approach to path planning for humanoid robots that computes dynamically-stable, collision-free trajectories from full-body posture goals. Given a geometric model of the environment and a statically-stable desired posture, we search the configuration space of the robot for a collision-free path that simultaneously satisfies dynamic balance constraints. We adapt existing randomized path planning techniques by imposing balance constraints on incremental search motions in order to maintain the overall dynamic stability of the final path. A dynamics filtering function that constrains the ZMP (zero moment point) trajectory is used as a post-processing step to transform statically-stable, collision-free paths into dynamically-stable, collision-free trajectories for the entire body. Although we have focused our experiments on biped robots with a humanoid shape, the method generally applies to any robot subject to balance constraints (legged or not). The algorithm is presented along with computed examples using both simulated and real humanoid robots.     

CAN总线在仿人机器人运动控制系统中的应用

文章先对CAN总线进行了介绍，然后把CAN总线应用到仿人机器人中，设计出一种适合仿人机器人的分布式运动控制系统，并给出了详细的设计过程。整个控制系统层次清晰，结构灵活，对仿人机器人的进一步发展具有积极的作用，同时为现场总线在仿人机器人中的应用提供了重要的参考。     

Humanoid Posture Selection for Reaching Motion and a Cooperative Balancing Controller

Our goal in this research was to develop a motion planning algorithm for a humanoid to enable it to remove an object that is blocking its path. To remove an object in its path, a humanoid must be able to reach it. Simply stretching its arms, which in a humanoid are shorter than its body and legs, is not sufficient to reach an object located at some distance away or on the ground. Therefore, reachability has to be ensured by a combination of motions that include kneeling and orienting the pelvis. However, many posture selection options exist because of the redundancy of a humanoid. In this research, we focused on the optimization of the posture of a humanoid that is reaching toward a point. The posture selected depends on the initial posture, the location of the point, and the desired manipulability of the humanoid’s arms. A cooperative balancing controller ensures the stability of the reaching motion. In this paper, we propose an algorithm for reaching posture selection and a balancing controller for humanoids, and we present the results of several experiments that confirm the effectiveness of the proposed algorithm and controller.     

基于参数化最优的仿人机器人倒地运动控制

针对仿人机器人的倒地运动控制,用经典的参数化优化方法求得最优控制函数的一个近似解．然后, 利用参数化控制及强化技术,基于几个分段的常数去逼近最优解,再将最优控制问题转化为一系列参数优化问题． 利用该方法提出了仿人机器人倒地优化控制算法,并与遗传算法进行了比较．最后,通过仿真对算法进行了验证．     

Pivoting based manipulation by a humanoid robot

In this paper we address whole-body manipulation of bulky objects by a humanoid robot. We adopt a “pivoting” manipulation method that allows the humanoid to displace an object without lifting, but by the support of the ground contact. First, the small-time controllability of pivoting is demonstrated. On its basis, an algorithm for collision-free pivoting motion planning is established taking into account the naturalness of motion as nonholonomic constraints. Finally, we present a whole-body motion generation method by a humanoid robot, which is verified by experiments.     

Motion capture-based wearable interaction system and its application to a humanoid robot,AMIO

In this paper, we present a wearable interaction system to enhance interaction between a human user and a humanoid robot. The wearable interaction system assists the user and enhances interaction with the robot by intuitively imitating the user motion while expressing multimodal commands to the robot and displaying multimodal sensory feedback. AMIO, the biped humanoid robot of the AIM Laboratory, was used in experiments to confirm the performance and effectiveness of the proposed system, including the overall performance of motion tracking. Through an experimental application of this system, we successfully demonstrated human and humanoid robot interactions.