The Knee Joint Design and Control of Above-knee Intelligent Bionic Leg Based on Magneto-rheological Damper

The above-knee intelligent bionic leg is very helpful to amputees in the area of rehabilitation medicine. This paper first introduces the functional demand of the above-knee prosthesis design. Then, the advantages of the four-bar link mechanism and the magneto-rheological （MR） damper are analyzed in detail. The fixed position of the MR damper is optimized and a virtual prototype of knee joint is given. In the end, the system model of kinematics, dynamics, and controller are given and a control experiment is performed. The control experiment indicates that the intelligent bionic leg with multi-axis knee is able to realize gait tracking of the amputee＇s healthy leg based on semi-active control of the MR damper.

Hopping planning of the bionic leg mechanism driven by PAMs with biarticular muscle

Bionic robots are generally driven by motors.As robots driven by pneumatic artificial muscles(PAMs)have the advantages of light weight,good bionics and flexibility,more and more researchers have adopted PAMs to drive bionic robots.A kind of bionic leg driven by PAMs for hopping is proposed in this work.A 3-DOF bionic leg driven by 4 PAMs is designed by analyzing the biological structure and movement principles of frog legs,and 3 kinds of leg configuration with different PAMs arrangement is proposed.One biarticular muscle is used to increase the joint rotating range.The bracket pulley and PAMs for driving joint can effectively increase its rotating range.The rotating range of hip and knee joint driven by a biarticular muscle is simulated.The simulation results show that the biarticular muscle can transfer the movement of the hip joint to the knee joint and increase the rotating range of the knee joint.The greater the contraction of PAM,the greater the rotating range of joint.The bionic leg can perform planned step distance and step height of hopping.

A Deep Neural Network Model for Upper Limb Swing Pattern to Control an Active Bionic Leg

Leg amputations are common in accidents and diseases.The present active bionic legs use Electromyography(EMG)signals in lower limbs(just before the location of the amputation)to generate active control signals.The active control with EMGs greatly limits the potential of using these bionic legs because most accidents and diseases cause severe damages to tissues/muscles which originates EMG signals.As an alternative,the present research attempted to use an upper limb swing pattern to control an active bionic leg.A deep neural network(DNN)model is implemented to recognize the patterns in upper limb swing,and it is used to translate these signals into active control input of a bionic leg.The proposed approach can generate a full gait cycle within 1082 milliseconds,and it is comparable to the normal(a person without any disability)1070 milliseconds gait cycle.

Joint position control of bionic jumping leg driven by pneumatic artificial muscle

The bionic legs are generally driven by motors which have the disadvantages of large size and heavy weight.In contrast,the bionic legs driven by pneumatic artificial muscles(PAMs)have the advantages of light weight,good bionics and flexibility.A kind of bionic leg driven by PAMs is designed.The proportional-integral-derivative(PID)algorithm and radial basis function neural network(RBFNN)algorithm are combined to design RBFNN-PID controller,and a low-pass filter is added to the control system,which can effectively improve the jitter phenomenon of the joint during the experiment.It is verified by simulation that the RBFNN-PID algorithm is better than traditional PID algorithm,the response time of joint is improved from 0.15 s to 0.07 s,and the precision of joint position control is improved from 0.75°to 0.001°.The experimental results show that the amplitude of the change in error is reduced from 0.5°to 0.2°.It is verified by jumping experiment that the mechanism can realize jumping action under control,and can achieve the horizontal displacement of 500 mm and the vertical displacement of 250 mm.

Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

Fuzzy-GA PID controller with incomplete derivation and its application to intelligent bionic artificial leg

An optimal PID controller with incomplete derivation is proposed based on fuzzy inference and the geneticalgorithm, which is called the fuzzy-GA PID controller with incomplete derivation. It consists of the off-line part andthe on-line part. In the off-line part, by taking the overshoot, rise time, and settling time of system unit step re-sponse as the performance indexes and by using the genetic algorithm, a group of optimal PID parameters K*p , Ti* ,and Tj are obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-linepart, based on K; , Ti* , and T*d and according to the current system error e and its time derivative, a dedicatedprogram is written, which is used to optimize and adjust the PID parameters on line through a fuzzy inference mech-anism to ensure that the system response has optimal dynamic and steady-state performance. The controller has beenused to control the D. C. motor of the intelligent bionic artificial leg designed by the authors. The result of computersimulation shows that this kind of optimal PID controller has excellent control performance and robust performance.

Trajectory tracking control of the bionic joint of the musculoskeletal leg mechanism

Pneumatic artificial muscles(PAMs) have properties similar to biological muscles,which are widely used in robotics as actuators.It is difficult to achieve high-precision position control for robotics system driven by PAMs.A 3-DOF musculoskeletal bionic leg mechanism is presented,which is driven by PAMs for quadruped robots.PAM is used to simulate the compliance of biological muscle.The kinematics of the leg swing is derived,and the foot desired trajectory is planned as the sinusoidal functions.The swing experiments of the musculoskeletal leg mechanism are conducted to analyse the extension and flexion of joints.A proportional integral derivative(PID) algorithm is presented for controlling the flexion/extension of the joint.The trajectory tracking results of joints and the PAM gas pressure are obtained.Experimental results show that the developed leg mechanism exhibits good biological properties.

仿生四足六旋翼无人机自适应着陆性能分析

旋翼无人机在民用和军用领域被广泛应用,但传统橇式起落架在复杂地形下难以起降,为了扩大旋翼无人机的降落面积和应用范围,设计一种仿人腿式两级缓冲自适应起落架。通过对仿生腿的正逆运动学分析,提出一种自适应起落架姿态调整策略;建立仿生四足六旋翼无人机着陆动力学模型,基于多体动力学软件simcenter 3D开展着陆动力学仿真,并与传统橇式起落架进行着陆性能对比研究。结果表明:着陆腿式的两级缓冲自适应起落架及其姿态调整策略,能够使滚转角减小95.69%,过载系数降低34.06%,两级缓冲自适应起落架在面对复杂地形时具备主动调节姿态安全着陆的地形适应能力和极好的减震缓冲能力。

复杂地形下仿生轮腿式机器人位姿控制研究

丘陵山地地势复杂、地形多变,农机装备作业环境以倾斜角度较大的斜坡为主,传统农机装备在丘陵山区复杂地形下作业时效率低、稳定性差,甚至会出现侧倾、翻车等现象。本文从仿生机械设计角度出发,提出一种在丘陵山地复杂地形下能够自主实现位姿调平控制的轮腿式机器人平台,提升复杂地形下的作业稳定性和安全性。以昆虫后足为仿生机械设计对象,并结合多连杆机构原理,完成新型变行程轮腿机构及机器人平台的整体架构设计。采用D-H参数法分析了轮腿机构运动学特性,结果显示轮腿式机器人离地间隙最大调整量为574mm,具备较强的越障能力。在空间坐标系上定义轮腿式机器人空间姿态参数,推导得到机身姿态角与轮腿伸缩量之间的空间姿态模型,并设计了基于NSGA-Ⅱ的机身空间姿态逆解算法。基于空间姿态逆解算法构建了轮腿式机器人全向位姿调平位姿控制系统,包含机身调平控制器、“虚腿”补偿控制器和质心高度控制器,在复杂地形下行驶时能够控制轮腿式机器人俯仰角、侧倾角、接地力、质心高度等空间姿态参数,然后通过搭建的轮腿式机器人ADAMS-Matlab联合仿真模型完成了位姿控制系统算法仿真验证。在机器人样机上开展了离地间隙自动调整和机身全向位姿调平试验,试验结果表明,试验样机离地间隙最大调整量为574mm,同时在复杂地形下能够实现机身位姿全向自动调平,调平平均时间约为1.2s,调平平均误差为0.8°,位姿控制响应速度与调平精度能够满足实际工作要求。

Bionic Design and Simulation Analysis of Energy⁃Efficient and Vibration⁃Damping Walking Mechanism

African ostrich can run for 30 min at a speed of 60 km/h in the desert,and its hindlimb has excellent energy saving and vibration damping performance.In order to realize the energy⁃efficient and vibration⁃damping design of the leg mechanism of the legged robot,the principle of engineering bionics was applied.According to the passive rebound characteristic of the intertarsal joint of the ostrich foot and the characteristic of variable output stiffness of the ostrich hindlimb,combined with the proportion and size of the structure of the ostrich hindlimb,the bionic rigid⁃flexible composite legged robot single⁃leg structure was designed.The locomotion of the bionic mechanical leg was simulated by means of ADAMS.Through the motion simulation analysis,the influence of the change of the inner spring stiffness coefficient within a certain range on the vertical acceleration of the body centroid and the motor power consumption was studied,and the optimal stiffness coefficient of the inner spring was obtained to be 200 N/mm,and it was further verified that the inner and outer spring mechanism could effectively reduce the energy consumption of the mechanical leg.Simulation results show that the inner and outer spring mechanism could effectively reduce the motor energy consumption by about 72.49%.

足式越野机器人集群系统关键技术与应用展望

足式机器人作为典型的地面移动机器人之一,其越野能力和智能水平不断提升,将足式越野技术与集群技术深入融合,是未来无人化装备发展的重要趋势之一。首先分析了群体仿生学机理、单体足式越野机器人、集群感知与协作和集成演示与应用等方面的研究现状,提出了足式越野机器人集群系统面临的技术挑战和科学问题,从足式越野机器人高机动越野、群体自组织机理与集群协作决策控制、群体协同态势感知和通讯自组网与应用验证四个方面深入剖析了亟待解决的核心关键技术,最后对足式越野机器人集群在军民领域的发展前景提出了设想和建议。

仿生六足机器人柔顺腿研究

为探索弧形腿柔顺性对仿生六足机器人运动性能的具体影响,首先使用伪刚体模型描述弧形腿的变形特征,并给出了刚度的数学表达;然后基于该刚度模型,在Webots仿真环境中构建虚拟样机,通过设定弧形腿不同的刚度,分析了仿生六足机器人在运动速度、能量消耗等方面的变化;最后通过制作不同刚度的弧形腿在物理样机中进行了验证。研究结果表明,弧形腿的柔顺性可以用伪刚体模型准确描述,它可提高仿生六足机器人的运动速度并减小能量消耗。

基于Hill肌肉模型的仿袋鼠腿悬架控制特性研究

为进一步改善车辆悬架的控制性能,采用仿生设计思想,提出一种基于Hill肌肉模型的仿袋鼠腿悬架(下称仿生悬架)。设计了该悬架的Fuzzy、Fuzzy-PID控制器,并采用ADAMS和Simulink联合仿真对其控制特性开展研究。研究发现:①冲击路面下,相对于被动悬架,Fuzzy控制和Fuzzy-PID控制下的车身位移和车身加速度分别下降了54%、58%和92%、93%,悬架抗冲击性能明显改善。②随机路面下,随着路面等级和车速的增加,Fuzzy控制和Fuzzy-PID控制均可有效改善悬架的控制性能;相对于被动悬架,主动控制下的悬架表现出更加优异的缓冲隔振性能、路面适应性及稳定性;主动控制下的车身加速度传递率(8.8%~1%)呈下降趋势且数值较小,轮胎动位移(0.19~3.92)mm及其传递率(8.1%~10.5%)呈上升趋势,但数值及变化较小。③冲击路面和随机路面下,相较于Fuzzy控制,Fuzzy-PID控制下的悬架特性更优。上述结果表明,基于Hill肌肉模型的仿生悬架具有良好的控制特性,验证了该仿生思路和控制方法的正确性和有效性。

无人直升机六足式起落架设计与控制算法

无人直升机在作战、巡逻、反潜、救援、运输中发挥极其重要的作用,但是传统起落架形式对起降环境要求较高。针对复杂地形自适应起落、恶劣海况舰面起降和停放以及应急坠撞高生存力等问题,提出了一种基于多连杆机构设计的无人直升机仿生腿式起落架系统,并完成了控制算法研究和建模仿真。首先从仿生腿数量、分布形式、腿部自由度配置和需要完成的功能等方面对仿生腿式起落架机械构型进行分析,并完成了六足式起落架运动学和动力学分析。然后针对仿生腿式起落架自适应着陆过程,完成着陆缓冲和地形建模算法的研究。最后,基于控制算法搭建虚拟样机仿真模型,完成了多种地形的仿真分析和样机测试。研究结果表明,所设计的仿生腿式起落架结构和控制算法可完成动态自适应着陆,实现着陆过程的平稳缓冲。

基于近似模型的重载仿生腿多目标优化

针对大型六足机器人在运动过程中腿部刚度不足和振动的问题,提出一种基于近似模型的多目标综合优化方法.建立有限元模型,分析各类复杂工况下腿部结构强度、刚度和模态频率等性能,确定仿生腿的优化空间.对仿生腿静态及动态性能建立参数化模型,定义相应的设计变量,采用优化拉丁超立方方法分别对仿生腿基节、大腿和小腿模块进行试验设计,获取初始样本点,拟合各模块响应面模型、克里格模型和径向基函数神经网络模型,通过误差分析选定精度最高的近似模型,并联合第二代非支配排序遗传算法,以静态刚度、质量和首阶固有频率为目标,约束最大应力,对仿生腿进行优化设计,对优化后的结果进行分析验证.结果表明,重载仿生腿经所述方法优化后,在满足结构强度的前提下,平地工况最大变形下降9.73%,斜坡工况最大变形下降9.46%,首阶固有频率提升3.45%,仿生腿总体质量下降8.63%.

一种弹性足式机器人腿部结构设计与分析

针对足式机器人在实现奔跑、跳跃等极限运动时,腿部会受到地面较大反向冲击力的问题,使用仿生学方法以猫科动物腿部骨骼肌系统为仿生对象,通过引入变刚度弹性杆件对闭链连杆机构进行优化设计,设计一种结构简单、能够有效储存地面反向冲击力并将其转化为运动时动能的足式机器人腿部机构;建立数学模型,对变刚度弹性元件进行定量分析,并采用矢量回路法对连杆机构进行运动学分析;建立优化前后两种单腿机构的虚拟样机,使用MATLAB软件设计控制系统,并应用ADAMS对虚拟样机进行行走、跳跃仿真,对优化前后两种腿部机构进行对比实验;在此基础上搭建实物样机,并进行实验验证。实验结果表明:所提出的足式机器人腿部结构具备可实现性,能够将来自地面的冲击力转化为运动的动能,提升足式机器人的跳跃高度。

基于连杆构型的守宫用移动关节仿生设计

为提升仿生壁虎的机动性与越障能力,设计开发了一种具有两自由度驱动的腿足式移动关节仿生构型。以机构学原理为导引,将吸盘、舵机、平面连杆等与壁虎体态构造进行有机融合,构建基于特征的关节组件三维实体造型,在仿形设计基础上实现了腿足关节的运动功能模拟。通过大、小腿关节联动轨迹仿真,验证了传动设计的正确性与可行性,同时分析了仿生关节的角动摆幅(0~73°)和越障高度(>30 mm)。静力学分析结果显示,不同承载环境(如平地、倒挂、垂壁)下的仿生关节符合强度和刚度设计要求。机体实验测试表明,该仿生关节运动平稳、传力可靠,具有良好的仿生机动性能。本研究为仿生壁虎移动技术探索开拓了新思路。

仿生轮腿式爬梯底盘结构设计分析与应用

针对现有的以履带组合式、升降伸缩式、行星轮式、连杆式为底盘的爬梯装置在克服台阶等障碍物时统一存在的水平不稳定、动力消耗大和操作较难等问题,该文设计了一款可实现自调节底盘保持恒水平稳定的仿生轮腿式爬梯底盘结构。提出了以该结构为应用点的辅助老人上、下楼装置,完成了其机械结构方案设计、控制逻辑方案设计和核心零部件的运动学仿真分析及强度校核。基于FTdesigner技术搭建出物理样机模型并开展原理性、功能性和稳定性测试研究,试验与仿真数据表明,该装置完全自适应调节座椅水平度,具有功耗低、便捷度高、稳定性强等特点。

四足仿生巡检机器人在上湾选煤厂的应用

为解决生产系统核心设备依靠人工巡视和检查的问题,上湾选煤厂在智能化建设过程中研发了具备自主行走、自主定位、自主导航、故障诊断等功能的四足仿生巡检机器人,通过对该机器人的多层次巡检场景下路径规划、步态生成与步态转换等技术的研究,使其具备在选煤厂非结构化环境内精确定位和稳定行走的能力,且通过搭载多种传感器实现了对选煤厂生产现场有害气体、温度、湿度等环境因素的实时监测。实际应用结果表明,该机器人能够替代人工完成巡检任务,并具有环境检测、状态判断、异常分析及故障预警等功能。

基于STM32单片机的四足仿生蜘蛛机器人控制系统设计

以四足机器人为研究对象,针对四足机器人在复杂环境下稳定性较差、越障能力有限的问题,设计了一款新型的仿生蜘蛛。该控制系统设计主要包括硬件设计和软件设计,以STM32单片机为控制核心,通过PCA9685舵机控制板控制整体12个舵机。蜘蛛携带的MPU6050陀螺仪模块将蜘蛛整体的运行姿态实时反馈给中央控制器,由此调整每条腿的角度,实现整体平衡的控制。同时位于蜘蛛前方的HC-SR04超声波模块实时监控前方障碍物的距离,进行避障处理。利用Protues仿真环境分析其各项功能的可行性,并进一步完成实物的设计制作与测试。仿真与实物测试结果表明:该系统能够较好地完成预期功能,实现在非结构地形上的平衡控制、躲避障碍物、运载物资等功能,为提升四足机器人的稳定性提供了较好的解决方案。