双足步行机器人的步态规划

主要研究了双足步行机器人的基本步态的建立过程,进行了参数化处理,提出了一种简单可行的步态规划方法,并对数据结果进行了仿真验证。仿真及试验结果表明,该文给出的方法能实现不同步速的连续动态步行。通过标准步态数据的建立,为实时步态规划校正和在线控制补偿算法奠定了基础。     

小型双足步行机器人的步态规划

为了解决双足步行机器人的步态控制,实现机器人稳定步行.为加强机器人的行走稳定性和优化步态过程,通过构造机器人行走过程中应满足的约束条件,规划机器人行走时的基本姿态及重心轨迹.根据规划的行走姿态及轨迹建立运动学方程,求解方程得到机器人各关节的运动轨迹.通过Matlab软件进行对运动轨迹模型的仿真,仿真得到的结果与设想的结果一致,证明步行得到平滑的关节轨迹是平稳的,并验证了方法的可行性.     

面向仿人机器人自然步态规划的人体步行实验分析

自然步态规划方法是实现仿人机器人步态柔顺和能量优化的可行方法,该方法要求对人体步行及其平衡策略进行定量研究．本文分析自然步态规划方法的原理,建立了一套快捷有效的人体步态测试系统,并通过实验建立了人体步行的参数化数据库．实验结果揭示了人体步行的参数化特征及其平衡策略,对于仿人机器人的自然步态规划及控制提供了理论指导．结论特别指出,仅仅通过规划的方式实现仿人机器人的自然步态是不完备的,自然步态的实现必须同仿生控制策略相结合．同时实验结论对于仿人机器人的本体优化设计也提供了参考．     

一种双足步行机器人的步态规划方法

本文介绍了一种双足步行机器人的步态规划方法，以前向运动为例，详细介绍了先分阶段规划然后合成的方法，并讨论了行走过程中的冲击振动问题及减振措施，实验及仿真结果验证了这一规划方法的有效性。     

考虑综合步行约束的仿人机器人参数化3D 步态规划方法

给出了一种三维环境下双足行走的参数化步态规划方法,建立了仿人机器人13 质量块约束动力学模 型．考虑单腿支撑和双腿支撑无冲击连续切换的六点边界约束条件、可行步态物理约束条件以及ZMP 稳定性约束 条件,以关节输出力矩函数的二次型积分值最小作为优化指标,采用参数化步态优化方法,将复杂关节轨迹的规划 问题转化为分段多项式系数组成的有限参数向量的优化问题,得到了快速和慢速两组光滑无振动的优化步态．仿真 和样机实验验证了该方法的有效性．     

双足步行机器人转弯步态规划及其实现

针对双足步行机器人的转弯步态规划及其实现问题进行了研究.首先介绍了双足步行机器人转弯步态规划方法和所涉及的关键问题,包括关键点轨迹插值和逆运动学解算,然后给出了实现双足步行机器人转弯步态规划的具体步骤,最后通过对实验室新研制的双足步行机器人转弯运动进行仿真和实验研究,证实了本文所提出的几何约束加修正补偿的双足步行机器人转弯步态规划方法的有效性和可行性.     

双足机器人动态步行实时步态生成

针对双足机器人动态步行生成关节运动轨迹复杂问题,提出了一种简单直观的实时步态生成方案。建立了平面五杆双足机器人动力学模型,通过模仿人类步行主要运动特征并根据双足机器人动态步行双腿姿态变化的要求,将动态步行复杂任务分解为顺序执行的四个过程,在关节空间相对坐标系下设计了躯干运动模式、摆动腿和支撑腿动作及步行速度调整模式,结合当前步行控制结果反馈实时产生稳定的关节运动轨迹。仿真实验验证了该方法的有效性,简单易实现。     

仿人跑步机器人机构与步态规划综述

阐述了仿人跑步机器人研究的必要性,介绍了几款国外典型的仿人机器人机构设计和驱动系统设计,对仿人跑步机器人的步态规划问题进行了综述,并指出仿人跑步机器人领域的研究难点和未来研究方向。     

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．     

仿人机器人两步步态规划算法研究

为了进一步提高仿人机器人步行时的稳定性,通过对人类步行的研究,并从两足步行机的两步步态规划方法中得到启发,对仿人机器人步行也进行类似的两步规划,但由于结构上的不同,仿人机器人中采用加入上肢运动补偿的方式实现平衡.规划仿人机器人的运动姿态,然后根据零力矩点必须落在稳定区域的原则,对仿人机器人的上肢运动轨迹进行求解,通过这种加入上肢补偿的两步规划来实现仿人机器人的稳定步行.从实验结果可以看出,采用这种两足步态规划方法,在仿人机器人两足步行时,可以使机器人上肢与下肢协调运动,从而提高了步行的稳定性.     

Optimal sagittal gait with ZMP stability during complete walking cycle for humanoid robots

A parametric method to generate low energy gait for both single and double support phases with zero moment point（ZMP） stability is presented. The ZMP stability condition is expressed as a limit to the actuating torque of the support ankle, and the inverse dynamics of both walking phases is investigated. A parametric optimization method is implemented which approximates joint trajectories by cubic spline functions connected at uniformly distributed time knots and makes optimization parameters only involve finite discrete states describing key postures. Thus, the gait optimization is transformed into an ordinary constrained nonlinear programming problem. The effectiveness of the method is verified through numerical simulations conducted on the humanoid robot THBIP-I model.     

Clock-turning gait synthesis for humanoid robots

Turning gait is a basic motion for humanoid robots. This paper presents a method for humanoid tuming, i.e. clock-turning. The objective of clock-turning is to change robot direction at a stationary spot. The clock-turning planning consists of four steps： ankle trajectory generation, hip trajectory generation, knee trajectory generation, and inverse kinematics calculation. Our proposed method is based on a typical humanoid structure with 12 DOFs （degrees of freedom）. The final output of clock-turning planning is 12 reference trajectories, which are used to control a humanoid robot with 12 DOFs. ZMP （zero moment point） is used as stability criterion for the planning. Simulation experiments are conducted to verify the effectiveness of our proposed clock-turuing method.     

Optimal sagittal gait with ZMP stability during complete walking cycle for humanoid robots

A parametric method to generate low energy gait for both single and double support phases with zero moment point(ZMP) stability is presented. The ZMP stability condition is expressed as a limit to the actuating torque of the support ankle, and the inverse dynamics of both walking phases is investigated. A parametric optimization method is implemented which approximates joint trajectories by cubic spline functions connected at uniformly distributed time knots and makes optimization parameters only involve finite discrete states describing key postures. Thus, the gait optimization is transformed into an ordinary constrained nonlinear programming problem. The effectiveness of the method is verified through numerical simulations conducted on the humanoid robot THBIP-I model.     

Robust recursive linear quadratic regulator for wheeled mobile robots based on optical motion capture cameras

In this paper, we deal with nonholonomic wheeled mobile robots (WMR) modeled as uncertain nonlinear systems. Sources of uncertainties can be due to erroneous estimation of mass, inertia, and center of gravity and due to payload time‐varying. They also can be considered as external disturbances generated from unstructured environments. We are proposing the use of a robust linear quadratic regulator (RLQR) to deal with tracking problems of WMR. In order to guarantee the effectiveness of this control approach, the robot posture is measured through a high‐precision motion capture system. This RLQR encompasses in a unified framework all state and output uncertain parameters of the system and does not depend on any auxiliary parameter to be tuned. It is useful to be used in online applications. Experimental results are presented with a comparative study among the R‐LQR, the nonlinear control via game theory, and the standard proportional‐derivative controller plus computed torque (PD+CT).     

Cane-supported walking by humanoid robot and falling-factor-based optimal cane usage selection

In this study, we propose a scheme that enables a humanoid robot to perform cane-supported walking and to select the optimal cane usage depending on its condition. A reaction force is generated through the cane–ground interaction. Although the optimal cane–ground contact position leads to the most effective reaction force from the viewpoint of the walking capability, the cane position is constrained during such contact. Thus, different cane utilities can be achieved based on the priority assigned to the reaction force and cane position. In this light, we propose cyclic, leg-like, and preventive usages, each of which has different priorities. These different priorities lead to different utilities such as the expansion of the support polygon, load distribution, and posture recovery. The robot selects the most suitable of these three cane usages using a selection algorithm for locomotion that is combined with Q-learning (Us-SAL). Through simulations, the robot is made to learn the affinities between these cane usages and falling factors as Q-values and to accordingly select the optimal cane usage. As a result, the robot can perform the desired walking by selecting the optimal cane usage depending on its condition. We conducted walking experiments for each cane usage and found that each improved the walking stability for a suitable falling factor. Furthermore, we experimentally validated Us-SAL; the robot selected the optimal cane usage depending on its condition and walked in a complex environment without falling.     

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.     

多移动机器人系统运动协调研究综述

运动协调是多移动机器人系统领域的主要研究热点之一。在阐述多机器人合作与运动协调两者关系的基础上,给出了多机器人系统运动协调的问题描述及其分类;从主要研究方法的角度,归纳总结了多机器人系统运动协调的国内外研究动态。最后,对运动协调在多移动机器人系统领域的前景和研究方向作出了展望。     

Equilibrium analysis of multi-limbs walking and climbing robots

The paper discusses the complex problem of assessing online the static equilibrium of statically-indeterminate climbing and walking robots (CLAWARs) with quasi-static locomotion. The method proposed is general and works for whatever number of legs and ropes operated by actuated winches connecting the robot to the environment. The configuration of the robot is assigned. First, the compliance of the robot body, of the legs and the compliances of the ground and the ropes are modeled as localized elasticities. The static equilibrium problem of the resulting model is statically-determinate under the hypothesis that the foot and rope points (where the ropes are fixed to the robot body) are joined to the ground by bilateral constraints. Since these constraints are unilateral (the feet are contact points and can detach from the ground, and the ropes can become slack), it is necessary to apply an iterative solving procedure in order to solve the static equilibrium problem. The method presented in the paper is a fast and effective alternative to nonlinear analysis of a finite element model of the robot at any assigned configuration. As an example, we consider the case of the heavy-duty CLAWAR Roboclimber.     

仿人机器人步态规划反馈控制研究综述

仿人机器人步行稳定性是机器人领域重要研究内容之一。介绍了仿人机器人常用的步态规划方法,划分为非反馈式和反馈式的两种步态规划算法。总结了反馈式步态规划主要研究的内容,并以世界著名Asimo、HRP、KHR和Darmstad仿人机器人为例,描述仿人机器人具体反馈控制方法和过程。探讨了仿人机器人步态反馈控制中有待研究的内容。     

High-speed laser localization for mobile robots

This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computation time. The efficiency is achieved by a closed-form solution for the matching of two laser scans, the use of natural scan features and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.