Verification of additional merits of a bimanual-coordinated rehabilitation robot using near-infrared spectroscopic technology

Using our designed robot, previous work has confirmed that bimanual training induced greater oxygenated-hemoglobin concentration than unilateral-limb training. However, the inter-hemispheric asymmetry of oxygenated-hemoglobin concentration was not compared between the bimanual and unilateral-limb patterns. To confirm the merits of our designed robot based on cerebral hemoglobin activation, 18 healthy subjects performed bimanual and unilateral-limb tasks in active-resisted mode and active-assisted mode for the right and left control sides (determines from that which limb provides a larger force). Analyses of variance were performed to compare the laterality index (LI) of two hemispheres between the two control sides, and to compare oxygenated-hemoglobin concentration between the different training patterns. The difference of LI between the two control sides was distinct in unilateral-limb patterns (p?=?0.029) but not obvious in bimanual patterns. As for the oxygenated-hemoglobin, active-resisted tasks induced a higher concentration than active-assisted tasks in the left control side (p?=?0.048). Results demonstrated that the proposed bimanual training induced the functional integrity of two hemispheres, and the robot is favorable for improving bimanual movement-coordination function. Additionally, active-resisted tasks had a higher difficulty level than active-assisted task. Therefore, the robot has a potential for delivering strength enhancement training in bimanual patterns.     

Control system design of a 3-DOF upper limbs rehabilitation robot

This paper presents the control system design of a rehabilitation and training robot for the upper limbs. Based on a hierarchical structure, this control system allows the execution of sequence of switching control laws (position, force, impedance and force/impedance) corresponding to the required training configuration. A model-based nonlinear controller is used to impose the desired environment to the patient's arm. The knowledge of robot kinematics and dynamics is thus necessary to ensure haptic transparency and patient safety. The identification process of robot dynamics is emphasised and experimental identification results are given for the designed robot. The paper also presents a particular rehabilitation mode named Active-Assisted. Simulation results of this rehabilitation mode illustrate the potentialities of the overall control scheme, which can also be applied to other rehabilitation robots.     

虚拟现实技术在柔性上肢康复机器人中的应用

根据末端牵引式和外骨骼式上肢康复机器人的特性,研制了一种新型的柔性上肢康复机器人。机器人的康复训练系统结合了主动和被动模式的要素,将虚拟现实（VR）技术引入上肢康复机器人,通过现实环境中的光学3D位置捕获以及VR环境中的3D位置感知,设计了虚拟动态模型交互性节点和碰撞检测实验,实现虚拟现实交互,提高虚拟模型运动实时效果和上肢康复训练精度。VR和新颖的康复机器人的集成为具有特定任务的患者提供了有效的训练。     

Control System Design for an Upper-Limb Rehabilitation Robot

Control system implementation is one of the major difficulties in rehabilitation robot design. The purpose of our study is to present newly developed control strategies for an upper-limb rehabilitation robot. The Barrett WAM Arm manipulator is used as the main hardware platform for the functional recovery training of the past-stroke patient. Passive and active recovery training have been implemented on the WAM Arm. A fuzzy-based PD position control strategy is proposed for the passive recovery exercise to control the WAM Arm stably and smoothly to stretch the impaired limb to move along predefined trajectories. An adaptive impedance force controller is employed in the active motion mode in which a fuzzy logic regulator is used to adjust the desired impedance between the robot and impaired limb to generate adaptive force in agreement with the change of the impaired limb's muscle strength. In order to evaluate the change of the impaired limb's muscle power, the impaired limb's mechanical impedance parameters as an objective evaluation index is estimated online by using a recursive least-squares algorithm with an adaptive forgetting factor. Experimental results demonstrate the effectiveness and potential of the proposed control strategies.     

下肢康复机器人的自适应人机交互控制策略

针对康复机器人运动过程中的人机交互性问题,提出一种下肢康复机器人自适应人机交互控制策略.提取伸屈运动中下肢表面肌电信号（Surface electromyography,sEMG）和足底压力特征,分别用于表征下肢运动意图和人机交互力（Interaction force,IF）信息,建立基于sEMG-IF的人机交互信息融合模型,实现下肢康复机器人运动轨迹的在线规划;考虑主动康复运动过程中的人机交互作用,建立具有时变动态特性的人机系统动力学模型,设计间接模糊自适应控制器对期望轨迹进行跟踪控制,实现下肢康复机器人自适应人机交互控制.通过对5名被试者进行下肢康复机器人运动控制实验研究,验证所提方法的可行性和有效性.     

基于无模型自适应的外骨骼式上肢康复机器人主动交互训练控制方法

设计了一种基于无模型自适应的外骨骼式上肢康复机器人主动交互训练控制方法.在机器人与人体上肢接触面安装力传感器采集人机交互力矩信息作为量化的主动运动意图,设计了一种无模型自适应滤波算法使交互力矩变得平滑而连贯;以人机交互力矩为输入,综合考虑机器人末端点与参考轨迹的相对位置和补偿力的信息,设计了人机交互阻抗控制器,用于调节各关节的给定目标速度;设计了将无模型自适应与离散滑模趋近律相结合的速度控制器完成机器人各关节对目标速度的跟踪.仿真结果表明,该控制方法可以实现外骨骼式上肢康复机器人辅助患者完成主动交互训练的功能.通过调节人机交互阻抗控制器的相应参数,机器人可以按照患者的运动意图完成不同的主动交互训练任务,并在运动出现偏差时予以矫正.控制器在设计实现过程中不要求复杂准确的动力学建模和参数识别,并有一定的抗干扰性和通用性.     

基于阻抗模型的下肢康复机器人交互控制系统设计

为帮助下肢功能障碍患者进行康复训练,设计了下肢康复机器人。对于该机器人的控制,采用传统系统无法柔顺控制,导致机器人运动轨迹偏离预设轨迹。针对该现象,提出了基于阻抗模型的下肢康复机器人交互控制系统设计。通过分析总体控制方案,设计系统硬件结构框图。采用L型二维力传感器,确定两个方向的人机交互力。使用绝对值编码器安装在各个关节处,其输出值作为髋关节、膝关节、踝关节电机的转动位置,增量编码器安装在电机轴上,测量值用来作为后期控制方法的输入参数。构建阻抗控制模型,能够调节机器人位置和速度,具有消除力误差功能。依据此力矩对参考运动轨迹进行设计,实时获取患者康复训练的跟踪、主动柔顺和接近状态信息。在柔顺训练实验测出人机交互力,通过实验结果知,在检测到人体主动力矩异常时,系统能够重新优化轨迹,具有良好柔顺控制效果。     

Bionic control of exoskeleton robot based on motion intention for rehabilitation training

As the complexity of obtaining irregular daily motion trajectory during upper limb rehabilitation training, this paper proposes the bionic control method for the presented exoskeleton robot arm based on motion intention. Firstly, the collected motion signal is pre-processing by filtering. Then the motion intention and motion mode of the processed signal are classified by using the hierarchical multi-classification support vector machine. Meanwhile, the adaptive Hopf oscillator network based on dynamic learning is used for offline learning of joint motion trajectory, and the parameters of the reproduced signal in different motion modes are obtained. Finally, the corresponding parameters are transferred according to the user’s intention, and the oscillator network is reconstructed to realize the periodic motion control of rehabilitation training. With experimental verification, the proposed method can follow the human body’s motion intention and reproduce the daily motion trajectory of the upper limb. The results show it can be used to conduct rehabilitation training for the patient.     

具有手指外展辅助功能的康复机器人系统

手指外展是改善脑卒中患者手部功能最重要的运动之一,目前国内外柔性手部康复机器人的研究主要聚焦在手指的屈伸上,忽略了手指完全外展的重要性。为实现更好的康复效果,研制了一款具有手指外展辅助功能的康复机器人系统。基于热塑性聚氨酯(TPU)薄膜涂层织物设计了一种新型外展驱动器。推导出外展驱动器一般力学方程,以表征其输出力矩与几何参数和内部气压的函数关系。性能分析结果表明,该驱动器可以在较低的气压下提供足够的外展力,具有辅助手指外展的可行性。招募了10名健康受试者进行日常生活活动(ADL)实验,在肌电信号监测下,验证了外展驱动器的辅助作用。此外,提出的康复系统将手部康复机器人与多功能被动训练模式相结合,通过配套软件,为脑卒中患者提供了更高效的康复训练。     

Fuzzy target tracking control of autonomous mobile robots by using infrared sensors

The theme of this paper is to design a real-time fuzzy target tracking control scheme for autonomous mobile robots by using infrared sensors. At first two mobile robots are setup in the target tracking problem, where one is the target mobile robot with infrared transmitters and the other one is the tracker mobile robot with infrared receivers and reflective sensors. The former is designed to drive in a specific trajectory. The latter is designed to track the target mobile robot. Then we address the design of the fuzzy target tracking control unit, which consists of a behavior network and a gate network. The behavior network possesses the fuzzy wall following control (FWFC) mode, fuzzy target tracking control (FTTC) mode, and two fixed control modes to deal with different situations in real applications. Both the FWFC and FTTC are realized by the fuzzy sliding-mode control scheme. A gate network is used to address the fusion of measurements of two infrared sensors and is developed to recognize which situation is belonged to and which action should be executed. Moreover, the target tracking control with obstacle avoidance is also investigated in this paper. Both computer simulations and real-time implementation experiments of autonomous target tracking control demonstrate the effectiveness and feasibility of the proposed control schemes.     

康复机器人患肢参数的在线辨识

根据患肢训练时力和位置等信息反馈,提出用解超定方程组的方法在线辨识患肢的动力学参数,实现患肢动力学模型的在线辨识,为远程康复训练机器人系统的实时控制提供较为准确的依据.仿真实验验证,该方法能较好地改善系统的动态性能,使系统具有较好的稳定性和鲁棒性.     

下肢康复机器人系统设计与协调控制算法

脑卒中、脊髓损伤、下肢退行性关节疾病等神经系统疾病会导致肢体功能障碍,需要进行有针对性和重复性的训练.本文设计了一款可以切换坐、立、躺三种模式的轮椅式下肢康复机器人,在机器人站立姿态的主动步行训练模式下,解算人体前进速度映射轮椅式底盘电机速度,实现了下肢功能障碍患者步态训练与机器人轮椅式车体的协调控制.实验结果表明,下肢外骨骼行走的速度曲线和轮椅式车体的速度曲线基本一致,实现人与机器人的协调控制.     

A robot test-bed for assistance and assessment in physical therapy

This paper describes an experimental test-bed that was developed to assist and assess rehabilitation during physical and occupational therapy. A PUMA 260 robot was used with a controller and interface software developed in-house. The robot is designed to operate in two modes: (1) passive and (2) active. In the passive mode, the robot moves the subject's arm through specified paths. In the active mode, a subject guides the robot along a predefined path overcoming specified joint stiffness. In this mode, the controller compensates for gravity so that the robot can support its own weight in an arbitrary configuration. The developed graphical interface enables display of the current configuration of the robot in real-time, and allows us to customize experiments for a subject, and collect force and position data during an experiment. The results of a preliminary study with healthy subjects using this test-bed are also presented along with issues involved in the choice of paths and interpretation of the results.     

基于力阻抗模型的上肢康复机器人交互控制系统设计

传统上肢康复机器人交互控制系统受到奇异位形影响,导致系统控制精准度较低,为此提出基于力阻抗模型的上肢康复机器人交互控制系统;设计上肢康复机器人交互控制系统结构,选取双串口12CSA60S2系列单片机作为下位机控制核心模块,利用椎齿轮改变驱动力方向,设计机械臂肘部结构,通过同步带传动,将器件隐藏于空手柄中;设计机械臂腕部结构,满足临床康复时上肢患者站姿与坐姿训练需求;选择箔式应变片BF350力传感器,设计电阻应变片桥接电路,处理传输信号;构建机器人目标阻抗模型,设计基于力阻抗控制策略,调节位置、速度和关节;为改善奇异位形情况,在奇异位形附近关节角速度指令直接由各个关节力矩阻尼控制得到,实现角速度精准输出,完成系统控制;由实验结果可知,该系统直线运动位置、旋转关节位置和伸缩关节位置跟踪结果与标准值基本一致,满足系统设计需求。     

多机器人主—从行星式编队控制

研究了二阶积分器描述的多机器人主—从行星式编队控制问题,提出了将多机器人编队分解为每个机器人对各自具有时变速度的虚拟机器人的跟踪控制,使得每个机器人相对于虚拟机器人的位置与速度跟踪误差收敛为零且彼此不相碰撞,此时编队系统收敛到理想队形.在统一的算法框架下,分别实现了跟随者以领航者为中心的公转运动编队(revolution formation,RF)模式和跟随者与领航者保持期望距离、期望速度的编队(desiredformation,DF)模式.公转运动编队(RF)模式适用于异构多机器人系统的环境探索任务;保持期望距离、期望速度的编队(DF)模式适用于自主水下机器人(AUV)、无人机(UAV)等合作与协调任务.应用李亚普诺夫稳定性理论对控制算法的稳定性进行了分析,并通过计算机仿真验证了该方法的有效性.     

一种新的康复与代步外骨骼机器人研究

针对老年人及下肢障碍者康复训练与代步问题,本文提出一种新的康复与代步外骨骼机器人.本文首先详细介绍了机器人各部分组成及机构设计方案,通过下肢外骨骼与轮椅的有机结合,有效保持或恢复老年人、脑卒中患者下肢运动能力的同时,为患者提供一种方便的代步工具;运用脚蹬车运动制订康复训练策略,可保持下肢康复训练轨迹固定,保证患者安全;提出主从式操作方法及多模态康复训练控制流程提高使用者参与感.最后通过仿真与实验验证了所提康复系统的可行性与设计的正确性.     

A Neuro-Sliding Mode Control Scheme for Constrained Robots with Uncertain Jacobian

The joint robot control requires to map desired cartesian tasks into desired joint trajectories, by using the ill-posed inverse kinematics mapping. In order to avoid inverse kinematics, the control problem is formulated directly in task space to gives rise to cartesian robot control. In addition, when the robot is constrained due to its kinematic mappings yields a stiff system and an additional complexity arises to implement cartesian control for constrained robots. In this paper, an alternative approach is proposed to guarantee global convergence of force and position cartesian tracking errors under the assumption that the jacobian is not exactly known. A neuro-sliding mode controller is presented, where a small size adaptive neural network compensates approximately for the inverse dynamics and an inner control loop induces second order sliding modes to guarantee tracking. The sliding mode variable tunes the online adaptation of the weights. A passivity analysis yields the energy Lyapunov function to prove boundedness of all closed-loop signals and variable structure control theory is used to finally conclude convergence of position and force tracking errors. Experimental results are provided to visualize the expected performance.     

机器人辅助上肢关节运动控制与临床实验研究

针对机器人辅助患肢被动康复训练过程中关节活动度(ROM)及运动控制参数不能随患肢病情实时调整的问题,提出一种新的模糊自适应关节被动运动闭环监督控制方法.该方法首先根据患肢关节活动恢复程度设计上层监督控制器,得到符合患肢病情的关节期望运动范围;再通过设计下层闭环位置跟踪控制器,控制机器人平稳地牵引患肢关节沿目标轨迹进行训练.临床实验结果验证了所提算法的有效性.     

矢量场逐次逼近的康复机器人柔顺交互控制

为了实现康复机器人的主动柔顺交互,提出了一种基于矢量场逐次逼近的控制模型;设计了矢量场逐次逼近系统,可输出机器人关节期望位移,该输出能与输入的扭矩、表面肌电及脑电等信号在振幅、频率和相位上保持同步,且通过调节遗忘因子参数值,可改变主动柔顺交互的积极性;利用自行设计的穿着型下肢康复机器人样机进行柔顺辅助实验,以验证所提出控制模型的有效性;通过FFT（Fast Fourier transformation）频谱对机器人关节扭矩的组成成分进行了分析,并采用基于最小二乘法的参数辨识方法实施了重力补偿,以便康复机器人实时控制.实验结果表明,该控制模型对于实现康复机器人与人之间的柔顺交互是有效的.     

基于遥感GIS信息融合的测绘机器人滑动模跟踪控制系统

测绘机器人是实现测绘自动化的执行设备,测绘机器人的工作空间更为复杂,给机器人的跟踪控制工作带来较大挑战。为提高测绘机器人跟踪控制效果,设计了基于遥感GIS信息融合的测绘机器人滑动模跟踪控制系统。加设遥感信息采集器和GIS信息采集器,改装遥感GIS信息处理器以及滑动模跟踪控制器,完成硬件系统的优化设计。考虑信息结构以及信息之间的逻辑关系,构建系统数据库,为遥感GIS信息提供充足的存储空间。根据测绘任务生成机器人滑动模移动轨迹,作为机器人的控制目标。采集测绘机器人实时遥感与GIS信息,利用遥感GIS信息融合技术跟踪机器人实时位姿,比对位姿跟踪结果与生成的控制目标,计算滑动模跟踪控制量,完成系统的测绘机器人滑动模跟踪控制软件功能优化。系统测试结果表明:设计系统的控制误差平均值为1.9 m,抖振幅值为0.8 dB,具有较好的控制效果。