四足机器人对角小跑步态非线性控制方法仿真

针对现有的四足机器人对角小跑步态控制方法存在的机器人运动速度较慢、灵活性较差等问题,提出了一种基于虚拟模型的四足机器人对角小跑步态非线性控制方法。方法需要构建一个四足机器人模型,并在该模型的工作范围内建立一个平面直角坐标系,在不考虑机器人足端车轮滑动的情况下,将驱动四足机器人的运动方程转换成矩阵的形式,寻找有界输入平动线速度和转动角速度,使矩阵在其控制下产生的误差可以在大范围内保持稳定。求解该四足机器人在工作平面坐标系中姿态误差的微分方程,构造该微分方程的Lyapunov函数并对其求导,根据求导结果设计一个四足机器人驱动控制器,通过该驱动控制器实现对四足机器人的对角小跑步态非线性控制。仿真结果表明,所提方法能够在快速、灵活的情况下实现对四足机器人对角小跑步态的非线性控制,且鲁棒性较高,能够满足用户需求。     

一种粗糙地形下四足仿生机器人的柔顺步态生成方法

传统以刚体动力学为基础的四足机器人运动控制方法对地形误差敏感,无法适应粗糙复杂地形,因此提出一种基于虚拟模型的运动控制方法用于实现四足机器人在粗糙地形下的行走.建立了以足底接触力为约束的高层步行任务和底层运动控制的映射关系.采用弹簧-阻尼-质量虚拟模型对四足机器人进行建模,将四足机器人的步行任务用一系列作用于机体质心的虚拟力去表征,基于各足等效力矩平衡的原则,将笛卡儿空间的虚拟力矢量分配到各支撑足,利用雅可比矩阵把足端力矢量转换为机器人关节空间的关节转矩.针对崎岖的空间3维粗糙地形,建立了机器人躯干姿态与地形的关联参数,通过调整躯干姿态有效扩大了机器人对粗糙地形的适应程度.运动仿真结果表明,机器人可以实现粗糙地形下稳定连续的行走,足底接触力平稳、无冲击,证明了该柔顺步态生成方法的合理性和有效性.     

一种基于并联6自由度结构的电动轮足机器人

针对现有基于串联式机械腿结构的四足机器人无法同时满足承载能力大、环境适应性强、运动速度快等要求的问题,提出了一种基于并联6自由度结构的电动轮足机器人结构原理,集成了轮式运动和足式运动各自的优势.在对机器人并联式轮腿进行运动学和动力学分析基础上,建立了单腿动力学模型和机器人整体运动学模型,提出了机器人机身姿态调整算法,有效提高了机器人运动过程中姿态的平稳性.仿真与实验验证了所提出的轮足复合式机器人的可行性和轮式运动时机器人机身姿态调整策略的有效性.     

四足机器人腿型配置的仿真分析与性能评价

对于四足机器人,腿型和关节姿态的布置形式极为重要,决定着机器人的运动学和动力学性能;四足机器人的腿型配置形式多样,为了在有效行走的前提下分析不同腿型配置的四足机器人的性能优劣和效率高低,采用基于CPG的仿生步态算法进行运动控制,通过Matlab/Simulink与Adams联合仿真,从速度、能耗和地形适应性三方面对不同腿型配置的四足机器人进行仿真分析和性能评价;通过对比仿真结果得知,前肘后膝型机器人前进速度更快,运动更平稳,横向偏移更小,能耗更低,具有更好的地形适应性,运动性能更优越,为物理样机调试与优化提供了理论依据。     

连续不规则台阶环境四足机器人步态规划与控制

为了实现四足机器人在无崎岖地形先验知识情况下的自主爬行,提出了一种四足机器人运动控制方法.该方法采用间歇爬行步态作为主步态,将爬行运动分解为若干任务分别进行控制:基于NESM(normalized energy stability margin)判据计算内外倾的稳定裕度并根据其比值进行质心位置调整;使用坐标映射的方式调整足端坐标进行地面坡度适应;通过调整各腿长度控制机器人的高度;利用姿态传感器信息进行姿态恢复.仿真和实验表明,机器人仅依赖内部传感器即实现了在崎岖地形稳定行走,验证了本文方法的有效性和可靠性.     

侧向推搡下的四足机器人复合抗扰控制策略

针对四足机器人侧向推搡下的平衡恢复问题,提出了一种复合抗扰反应式鲁棒控制策略.该策略由摆动相的自适应侧摆规划策略和支撑相的关节抗扰控制构成.摆动相自适应侧摆规划策略通过四足机器人足端落地点的力平衡条件进行主动式步态规划以保证机器人在侧向推搡下的姿态稳定,并基于关节输出力矩给出了侧摆的启动条件.支撑相关节抗扰控制通过带扰动项的四足机器人完整动力学模型设计了基于干扰观测器的鲁棒滑模控制器,实现对侧向推搡扰动的补偿.最后,通过Matlab与ADAMS联合仿真验证了提出的控制策略的有效性.     

基于群论的六足机器人运动空间研究

针对六足机器人相对复杂的机械结构,提出一个简化模型结构,利用等条件约束把腿支链转化为滑动连杆.其次,针对简化后的模型,依据其运动约束方程,分析研究六足机器人可达空间以及姿态空间.在群论基础上,结合六足机器人的运动约束模型,着重分析机器人初始状态的对称性与其运动空间对称性的关系,并通过分层搜索算法,求解六足机器人运动空间.最后通过仿真数据分析六足机器人运动空间随不同参数调整的变化情况,对比分析机器人不同初始状态与其运动空间的关系,同时对运动平台的姿态空间及其截面进行分析.分析与仿真结果表明,利用群约束模型可以对复杂并联机器人运动空间进行更详尽的分析,得到包括空间对称性、姿态空间以及空间截面的详细信息.     

面向复杂地形的四足机器人步态生成方法

为实现四足机器人在凹凸地形上稳定运动并能选择最大步长的目的,提出了基于稳定裕度的步态规划方法;基于研究对象,建立四足机器人的运动学方程及逆运动学方程,将机器人足端的位置映射为各关节的关节变量;提出工作空间矩阵的概念,将所需克服的地形高度反映到工作空间矩阵中,并选择最优步态区域;依据四足机器人的立足点在质心坐标系下的空间坐标,以纵向稳定裕度为约束条件,在工作空间矩阵中计算机器人摆动腿的最大步长并规划机械腿的运动轨迹;针对所提出的方法,分别利用MATLAB和ADAMS进行仿真验证;在MATLAB环境中计算并验证质心的水平投影是否在立足点形成支撑多变形内,而ADAMS平台分析机器人在复杂地形上的位移变化及姿态变化。仿真结果表明机器人的质心始终在支撑多边形内,机器人的躯干姿态基本保持不变且运动速度匀速,所提出的方法能够保证机器人稳定行走,为四足机器人的稳定运动提出依据。     

四足机器人对角小跑起步姿态对稳定步行的影响

对四足机器人对角小跑步态下绕支撑对角线的翻转力矩建立了力学模型，分析了该力矩对机器人运动姿态及稳定步行的不利影响，并提出了利用起步姿态来削弱翻转力矩不利影响的方法——三分法．     

足式机器人在非结构地形中的姿态求解算法

为了改进传统足式机器人姿态求解算法的不足,提出了一种新型的适用于非结构地形的姿态求解方法.该算法将动力学分析得到机体运动加速度信息与惯性测量单元（IMU）的信息相融合,通过卡尔曼滤波器计算机器人机体的姿态信息.所提的算法也适用于机器人机体存在冲击力的情况。为了验证算法的有效性,对两款典型的足式机器人在非结构地形中的运动进行了仿真,结果表明提出的算法能够准确的求解出机器人的姿态信息,具有良好的有效性和通用性。     

货叉运动机械冲突光电型检测装置

为了准确检测堆垛机货叉伸缩时是否与其他物体发生机械冲突,防止冲突造成损害,设计了一种无连线型机械冲突检测装置.装置由偏振滤波型光电传感器、梳齿挡块和多块反射板构成.安装在货叉侧面可滑动的梳齿挡块与物体发生冲突时将遮挡反射板.光电传感器通过检测反射板是否被遮挡来检测是否发生机械冲突.相对于基于摩擦离合器、过流检测以及以往的光电检测和保护方式,该装置不易漏检误检,且与货叉无连线.     

Dynamic stability in bipedal motion: Adaptive control strategies for balance and controlled motion

The exploration of dynamic stability in bidedal machines requires a great deal of knowledge about the science of balancing, both equilibrium and motion. Recent work in robotic legged locomotion has concentrated on systems that require three or more legs on the ground at any given time. This research focuses on adaptive control strategies for a bipedal machine that will allow balance and controlled motion with one leg and, if not walking, on two legs on the ground at any given time. Our approach is to optimize a set of balance and motion profiles through extensive simulation and to validate the profiles on an experimental testbed. Once validated as capable of providing dynamic stability, the adaptive control model uses these profiles as nominal control. The sensory input is then used to modify the nominal control to allow precise control at each sampling period. Simply stated, our control model continuously measures the rate of fall of the biped, and adjusts torques at the knees and hips to constrain this fall to dynamic balance and controlled motion. As should be suspected at this time, our control model is sensor driven and does not require a solution to the Lagrangian equations of motion. The result is a faster, less complex, adaptive control process. Our experimental bipedal testbed currently, and repeatedly, exhibits 25 + stable steps on a flat but slightly varied terrain. Current technology could not provide the kind of actuation and measurements necessary to implement our control model; therefore, our team has developed new low pressure, servoed hydraulic systems and sensory devices. Our most recent experimentation has used parallel computing methods and devices in the C + + programming language on a transputer (parallel computer) based Cogent XTM parallel computing workstation.

A new dimension to our research is the translation of our knowledge to manufacturing systems and machines. We are currently investigating how our knowledge of limb coordination and reflex can be applied to the coordination of multiple jointed appendages. In addition, we will explore the use of our positioning and balancing technology in the work cell.     

An investigation of underfoot accidents in a MAIM (Merseyside Accident Information Model) database

Underfoot accidents taken from a study of patient interviews have been analysed to investigate factors that may be implicated in the causes of the accidents. Within the sample of patients in this study women holding items are more at risk than men from underfoot accidents. Carrying items such as shopping and handbags may obstruct the line of sight to underfoot hazards, affect balance and adversely affect reflex corporal movements that may help prevent injury.     

Using results of eye movement signal analysis in the neural network recognition of otoneurological patients

We extracted a collection of eye movement signals employed for almost two decades in clinical otoneurological tests at a balance laboratory. During those years we designed and programmed signal analysis methods to analyse their features in detail and to compute medically important attributes. In the present study, using such attributes and their results computed we classified test cases into groups of healthy subjects and patients with multilayer perceptron neural networks. Classification succeeded in total accuracies from 60% to 90% depending on the type of eye movements, which were saccades, nystagmus, sinusoidal movements and vestibulo-ocular reflex stimulated in two different ways; these are the chief eye movement tests applied in otoneurology.     

Fuzzy control-based real-time robust balance for a humanoid robot

This paper studies and implements a real-time robust balance control for a humanoid robot under three environment disturbances which are an external thrust, an inclinable platform, and a see-saw. More precisely to say, the robot with robust control can resist an external thrust, stand on a two-axis inclinable platform, or walk on a see-saw successfully. The main feature of the robot is that it has a waist joint which has three degrees of freedom. With the aids of the proposed fuzzy controllers, the robot can change the posture of the body nimbly by adjusting the waist joint and two ankle joints to strengthen the stabilization capacity. The sensory system of the robot includes eight force sensors and one inertial measurement unit sensor in order to measure the center of pressure and the slant angle of the robot’s body. According to the measured data from the sensors and by imitating human reflex actions, the proposed fuzzy controllers perform real-time balance control for the robot under three environment disturbances. According to the experiment results, the stability of the robot is increased at least 32.2 and 61.7% under the first two environment disturbances, respectively. In addition, the robot walking on a see-saw has a success rate of about 95%.     

Development and testing of a prototype reflex measurement system employing artificial neural networks

This paper presents the development, testing and performance evaluation of a patellar tendon reflex measurement system to provide a quantitative reflex evaluation for use by medical practitioners and in a telemedicine or E-medicine environment. A prototype was developed that makes use of XSens MTx orientation sensors, force-sensitive resistors and an electromyogram to measure the reflex response. Suitable parameters from the sensors were identified for analysis, and clinical testing was performed on 20 subjects to collect data to evaluate the system's performance. Subjective reflex evaluations were conducted by three medical doctors according to a standard reflex grading scale using video recordings of the tests. Multi-layer feed-forward (MLFF) artificial neural networks (ANNs) were used to analyze the collected data with the aim of pattern identification and reflex grading prediction. It was found that the MLFF network delivered the corresponding reflex grading with an accuracy of 85%, which was of the same order as the rate of differences between the subjective reflex evaluations performed by the doctors (80%). The use of ANNs to analyze a reflex measurement offers a repeatable and concise representation of the reflex that is familiar to doctors and can be developed for use in a general clinical setting or for telemedicine purposes.     

Hadoop环境下基于数据本地化的Reduce任务调度策略

在MapReduce模型任务处理过程中,当Reduce任务开始执行,远程拉取Map阶段的输出数据时,会消耗大量的网络带宽,甚至会出现网络瓶颈问题。本文提出基于数据本地化和负载均衡的任务分配策略。该策略中用户首先设置采样数据量M,在Map阶段对前M个数据块进行采样;其次根据采样结果,同时考虑数据本地化因素,将Reduce任务进行分配;然后基于负载均衡将Reduce任务进行再分配,通过任务分配,系统生成一个任务分配表;最后启动Reduce任务,系统开始数据拉取,未被采样的数据根据任务分配表进行任务分配。通过大量实验验证,基于数据本地化和负载均衡的任务分配策略,既能减少Shuffle阶段数据的传输量,又能降低网络带宽的消耗,同时可以避免出现某些节点空闲而其它节点任务量大甚至处理不了的情况,从而提高了集群处理数据的整体能力。      

Sensory reflex control for humanoid walking

Since a biped humanoid inherently suffers from instability and always risks tipping itself over, ensuring high stability and reliability of walk is one of the most important goals. This paper proposes a walk control consisting of a feedforward dynamic pattern and a feedback sensory reflex. The dynamic pattern is a rhythmic and periodic motion, which satisfies the constraints of dynamic stability and ground conditions, and is generated assuming that the models of the humanoid and the environment are known. The sensory reflex is a simple, but rapid motion programmed in respect to sensory information. The sensory reflex we propose in this paper consists of the zero moment point reflex, the landing-phase reflex, and the body-posture reflex. With the dynamic pattern and the sensory reflex, it is possible for the humanoid to walk rhythmically and to adapt itself to the environmental uncertainties. The effectiveness of our proposed method was confirmed by dynamic simulation and walk experiments on an actual 26-degree-of-freedom humanoid.     

Motion Sickness Simulation Based on Sensorimotor Control

Sensorimotor control is an essential mechanism for human motions, from involuntary reflex actions to intentional motor skill learning, such as walking, jumping, and swimming. Humans perform various motions according to different task goals and physiological sensory perception; however, most existing computational approaches for motion simulation and generation rarely consider the effects of human perception. The assumption of perfect perception (i.e., no sensory errors) of existing approaches restricts the generated motion types and makes dynamical reactions less realistic. We propose a general framework for sensorimotor control, integrating a balance controller and a vestibular model, to generate perception‐aware motions. By exploiting simulated perception, more natural responses that are closer to human reactions can be generated. For example, motion sickness caused by the impairments in the function of the vestibular system induces postural instability and body sway. Our approach generates physically correct motions and reasonable reactions to external stimuli since the spatial orientation estimation by the vestibular system is essential to preserve balance. We evaluate our framework by demonstrating standing balance on a rotational platform with different angular speeds and duration. The generated motions show that either faster angular speeds or longer rotational duration cause more severe motion sickness. Our results demonstrate that sensorimotor control, integrating human perception and physically‐based control, offers considerable potential for providing more human‐like behaviors, especially for perceptual illusions of human beings, including visual, proprioceptive, and tactile sensations.     

Effects of hand vibration on reflex behaviors and pain perception – A pilot study

This research investigated the effects of hand vibration on the protective reflex responses and perception of the stimulus intensity. Electrical pulses were applied to the wrist to elicit the reflex responses. Changes of the reflex response were measured using the surface electromyographic activities from the hand flexor muscles, and were analyzed as a function of vibration frequency and initial level of grip force. Psychophysical experiment was also performed to assess the effects of hand vibration on perception of the electrical stimulus. The reflex responses were stronger during vibration, and were more visible at lower vibration frequencies and higher muscle contraction level. During vibration, a poor correlation was found between the reflex responses and stimulus perception.

Relevance to Industry

Results suggesting to adopt low level of grip exertion (light-weighted tool) and high vibration frequency to minimize the vibration-induced change of the protective reflex behaviors are useful to tool manufacturers and related workers.