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.

足式机器人马蹄型仿生足设计及垂向动力学研究

针对足式机器人行走垂向缓冲及越沙防陷的需求,借鉴马蹄高负载、广适应的生物特征,提出一种集金属靴、橡胶蹄球和可更换蹄掌为一体的马蹄型仿生足结构。在充分考虑足部结构自身材料非线性和接触非线性的基础上,对比分析了仿生足静刚度、动刚度、冲击特性及越沙防陷等垂向动力学性能。结果表明,仿生足能够有效缓冲行进过程中的足部冲击,外凸内凹的蹄掌设计能确保机器人具有良好的越沙性能,马蹄型仿生足垂向动力学性能总体优于原始足。

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%.

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。

四足机器人仿生腿增强碳纤维3D打印技术及其实验研究

为了提高四足机器人仿生腿的使用性能,使其腿部结构满足高承载、轻量化要求,提出一种以连续碳纤维(CCF)为增强材料,以短切碳纤维增强尼龙为基体材料的混合增强3D打印技术,通过样条拉伸实验对碳纤维复合材料的伸性能进行了验证。使用连续与短切碳纤维混合增强3D打印制备四足机器人仿生腿,对四足机器人常见4种工况进行了静力学仿真,选取两类典型工况进行载荷测试实验,可知在站立工况下承载力提升了19.05%,变形量减少了50.70%,在30°外展工况下承载力提升了3.14%,变形量减少了43.05%,且重量减轻了18.83%,验证了连续碳纤增强材料替代传统铝合金材料的可能性。

人工肌肉驱动仿生腿运动学建模与仿真研究

人工肌肉驱动仿生腿是一种新型智能假肢,用于补偿下肢截肢者残肢侧的运动功能。对人工肌肉驱动仿生腿进行运动学建模与仿真研究,通过拉格朗日法对仿生腿的支撑相和摆动相建立运动学模型,推导并计算仿生腿运动学及动力学方程,基于MATLAB和Adams软件进行运动学仿真。研究结果证明,所建立的人工肌肉驱动仿生腿模型可以实现假肢的拟人步态。

异构双腿机器人仿生腿的设计与控制实现

提出具有可变瞬时转动中心的多轴膝关节,由多轴4联杆机构组成,具有仿生相似性·建立仿生腿的动力学方程,通过求解逆动力学问题的方法,得出最优步态下的膝关节控制力矩·通过传感器获得步态信息,从计算机中选择与该步态模式相应的力矩控制程序,每种步态模式由学习系统产生·选用磁流变阻尼器(MRDamper)组成的仿生腿反应迅速,动作灵活,与人工腿的步态更对称、更协调·

基于混合驱动仿生膝关节机构设计

目的针对传统假肢关节机构与驱动系统的不足,设计并实现由磁流变阻尼器结合直流电机混合驱动,滚珠丝杠传动的多轴闭链仿生膝关节.方法通过多变量优化设计方法求解出膝关节机构参数、滚珠丝杠安装位置参数和电机的角速度及扭矩.基于虚拟样机技术构建了智能仿生腿的仿真平台并在其上进行了运动学仿真.结果仿生膝关节与人腿膝关节运动曲线接近,结合电机驱动可实现更大范围的步速调整.结论该优化方法得到的系统参数可使膝关节机构具有很高的仿生特性及良好的运动特性.

基于蚁群算法的智能人工腿最优PID控制器设计

以蚁群系统和蚁群算法为基础,提出了一种新的具有不完全微分的最优PID控制器的设计方法。该控制器以系统单位阶跃响应的超调量σ、上升时间tr以及调整时间ts为性能指标,针对给定的控制对象,利用所建立的蚁群算法搜索出一组最优PID参数K i及T d,作为实时控制中PID控制器的参数。该控制器被用于控制智能p,T 仿生人工腿中的执行电机。计算机仿真结果表明,与传统的PID控制器相比,这种基于蚁群算法的最优PID控制器具有良好的动态和稳态性能,可用于控制多种不同的对象和过程。

用磁流变阻尼器控制异构双腿机器人的仿真研究

介绍了磁流变阻尼器在异构双腿行走机器人中的新应用。首先给出了仿生腿选用MR阻尼器的依据,建立了修正的Sigmoid阻尼器模型;然后对阻尼器安装位置进行了优化;最后对BRHL进行了步态跟随优化及迭代学习控制仿真。结果表示,基于MR阻尼器控制的仿生腿能够很好的实现对人工腿的步态跟随,具有较好的仿人特性。

含半月板的假肢膝关节机构设计与减震性能分析

智能仿生腿是一种能够最大限度模仿人体健康腿运动的高级智能下肢假肢。当假肢穿戴者从事跑步、打网球等复杂运动时,运动对假肢关节的冲击和震动将大幅增加。为提高假肢抗冲击、震动性能,将人体膝关节半月板结构引入假肢膝关节。分析了人体膝关节的解剖结构和功能,进行了智能仿生腿膝关节机械机构设计,基于ANSYS对假肢膝关节半月板结构的抗冲击、震动性能进行了有限元分析。结果表明:半月板具有承载负荷的能力并具有缓冲吸震作用。

双菱形仿袋鼠腿悬架的PID和Fuzzy-PID控制特性研究

为改善传统车辆悬架的性能,借鉴自然进化而来的袋鼠腿部结构,提出一种双菱形仿袋鼠腿悬架。为研究该悬架的行为特性,采用Lagrange方程法推导其动力学模型;基于动力学模型分别设计其PID和Fuzzy-PID控制器;在MATLAB/simulink环境下,建立其被、主动仿真模型并开展特性仿真与分析。研究发现:①被、主动模式下,车身垂向加速度、悬架动挠度及轮胎动位移均方根,随着车速和路面等级的增加均有所增加且在允许范围内。②不同路面等级下,随着车速的增加,被、主动模式的车身垂向加速度传递率数值基本相同,均呈单调递减趋势,(如,被动模式的车身垂向加速度传递率在1.64%~0.80%之间变化),但主动模式优于被动模式,Fuzzy-PID控制优于PID控制(约下降0.5%~0.6%);③不同路面等级下,随着车速的增加,被、主动模式的轮胎动位移传递率数值均增加,但其增加率呈下降趋势。从传递率数值上看,主动模式明显优于被动模式(约减少15%~25%,高车速时下降明显),但Fuzzy-PID控制与PID控制效果基本相同;④由车身加速度、悬架动挠度和轮胎动位移传递率频响特性可知双菱形仿袋鼠腿悬架有两个峰值,第一个峰值在0.8 Hz附近,第二个峰值在15 Hz附近;主动控制下悬架的舒适性和稳定性均优于被动悬架,Fuzzy-PID较PID控制效果更佳。研究结果表明:所提悬架的结构设计合理、方案可行。该悬架具有良好的路面适应性、高速舒适性和稳定性,这些特性与袋鼠腿的运动特性相吻合,验证了该研究思路的正确性和控制方法的有效性。

一种仿蝗虫腿空间缓冲吸附机构缓冲参数研究

针对空间机器人在太空高速工况下,难以平稳地着陆且黏附在目标航天器表面的问题,提出了一种仿蝗虫腿非合作空间缓冲吸附机构。为了得到机构最优的缓冲参数,使得其与目标航天器碰撞时不发生回弹且减小碰撞力以保护自身,提出了空间缓冲吸附机构碰撞缓冲的动力学模型,该模型研究方法基于连续碰撞力方程。通过对空间缓冲吸附机构的腿部胫节、股节以及整机的受力分析,求得其不同受力工况下的动力学方程。采用线性弹簧阻尼结构等效空间缓冲吸附机构碰撞缓冲过程,建立空间缓冲吸附机构碰撞动力学模型,并结合实际碰撞缓冲参数设计出空间缓冲吸附机构碰撞过程的刚度系数和阻尼系数。最后利用动力学仿真进行校验,结果表明用此方法,机构所受碰撞力大幅减小且不发生回弹,证明了方法的合理性。