Multiple Measurement Models of Articulated Arm Coordinate Measuring Machines

The existing articulated arm coordinate measuring machines（AACMM） with one measurement model are easy to cause low measurement accuracy because the whole sampling space is much bigger than the result in the unstable calibration parameters. To compensate for the deficiency of one measurement model, the multiple measurement models are built by the Denavit-Hartenberg＇s notation, the homemade standard rod components are used as a calibration tool and the Levenberg-Marquardt calibration algorithm is applied to solve the structural parameters in the measurement models. During the tests of multiple measurement models, the sample areas are selected in two situations. It is found that the measurement errors＇ sigma value（0.083 4 ram） dealt with one measurement model is nearly two times larger than that of the multiple measurement models（0.043 1 ram） in the same sample area. While in the different sample area, the measurement errors＇ sigma value（0.054 0 ram） dealt with the multiple measurement models is about 40% of one measurement model（0.137 3 mm）. The preliminary results suggest that the measurement accuracy of AACMM dealt with multiple measurement models is superior to the accuracy of the existing machine with one measurement model. This paper proposes the multiple measurement models to improve the measurement accuracy of AACMM without increasing any hardware cost.

Dynamic Coordination of Uncalibrated Hand/Eye Robotic System Based on Neural Network

A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.

Flexible Scanning Method by Integrating Laser Line Sensors with Articulated Arm Coordinate Measuring Machines

Measuring and reconstructing the shape of workpieces have been considered as a fundamental step in both reverse engineering and product quality control.Owing to increasing structural complexity of recent products,measurements from multiple directions are typically required in current scanning techniques.Specifically,the plane structured light can be applied to measure one area of a part at a time,with an additional algorithm required to merge the collected data of each area.Alternatively,the line structured light sensor integrated on CNC machines or CMMs could also realize multi-view measurement.However,the system needs to be repeatedly calibrated at each new direction.This paper presents a flexible scanning method by integrating laser line sensors with articulated arm coordinate measuring machines(AACMM).Since the output of the laser line sensor is 2D raw data in the laser plane,our system model introduces an explicit transformation from the 2D sensor coordinate frame to the 3D base coordinate frame of the AACMM(i.e.,the translation and rotation the of the 2D sensor coordinate in the sixth coordinate system of AACMM).To solve the model,the“conjugate pairs”are proposed and identified by measuring a fixed point(e.g.,a sphere center).Moreover,a search algorithm is adopted to find the optimal solution,which noticeably boosts the model accuracy.The experimental results show that the error of the system is about 0.2 mm,which is caused by the error of the AACMM,the sensor error and the calibration error.By measuring a complicated part,the proposed system is proved to be flexible and facilitate,with the ability to measure a part expediently from any necessary direction.Furthermore,the proposed calibration method can also be used for robot hand-eye relationship calibration.

Adaptive neural network control for coordinated motion of a dual-arm space robot system with uncertain parameters

Control of coordinated motion between the base attitude and the arm joints of a free-floating dual-arm space robot with uncertain parameters is discussed. By combining the relation of system linear momentum conversation with the Lagrangian approach, the dynamic equation of a robot is established. Based on the above results, the free-floating dual-arm space robot system is modeled with RBF neural networks, the GL matrix and its product operator. With all uncertain inertial system parameters, an adaptive RBF neural network control scheme is developed for coordinated motion between the base attitude and the arm joints. The proposed scheme does not need linear parameterization of the dynamic equation of the system and any accurate prior-knowledge of the actual inertial parameters. Also it does not need to train the neural network offline so that it would present real-time and online applications. A planar free-floating dual-arm space robot is simulated to show feasibility of the proposed scheme.

Cortical activity in patients with high-functioning ischemic stroke during the Purdue Pegboard Test:insights into bimanual coordinated fine motor skills with functional near-infrared spectroscopy

After stroke,even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity,leading to reduced functional independence.Bilateral arm training has been proposed as a promising intervention to address these deficits.However,the neural basis of the impairment of functional fine motor skills and their relationship to bimanual coordination performance in stroke patients remains unclear,limiting the development of more targeted interventions.To address this gap,our study employed functional near-infrared spectroscopy to investigate cortical responses in patients after stroke as they perform functional tasks that engage fine motor control and coordination.Twenty-four high-functioning patients with ischemic stroke(7 women,17 men;mean age 64.75±10.84 years)participated in this cross-sectional observational study and completed four subtasks from the Purdue Pegboard Test,which measures unimanual and bimanual finger and hand dexterity.We found significant bilateral activation of the sensorimotor cortices during all Purdue Pegboard Test subtasks,with bimanual tasks inducing higher cortical activation than the assembly subtask.Importantly,patients with better bimanual coordination exhibited lower cortical activation during the other three Purdue Pegboard Test subtasks.Notably,the observed neural response patterns varied depending on the specific subtask.In the unaffected hand task,the differences were primarily observed in the ipsilesional hemisphere.In contrast,the bilateral sensorimotor cortices and the contralesional hemisphere played a more prominent role in the bimanual task and assembly task,respectively.While significant correlations were found between cortical activation and unimanual tasks,no significant correlations were observed with bimanual tasks.This study provides insights into the neural basis of bimanual coordination and fine motor skills in high-functioning patients after stroke,highlighting task-dependent neural responses.The findings also suggest that patients who exhibit better bimanual performance demonstrate more efficient cortical activation.Therefore,incorporating bilateral arm training in post-stroke rehabilitation is important for better outcomes.The combination of functional near-infrared spectroscopy with functional motor paradigms is valuable for assessing skills and developing targeted interventions in stroke rehabilitation.

基于ARM和DSP的实时谐波源定位仪的研制

本文在ARM(S344B0X)和DSP(TMS320LF2407A)搭建的硬件平台上实现了基于瞬时无功理论的谐波源定位。首先利用Park坐标变换,将三相的电网信号变换到以基波频率为转速的二相旋转坐标系统上,经过低通滤波器,分离信号的基波和谐波成分,再经过逆变换可以计算谐波部分的有功功率,从而确定谐波源。硬件部分主要包括电网信号的调理和采集,DSP,ARM以及双口RAM。通过与数字实时仿真系统(RTDS)的联调,检验了此定位仪的性能。

基于ARM的包装袋成型机嵌入式控制系统设计

目的为提高包装袋成型机的控制精度、实时性、系统集成度,基于ARM微控制器设计一种嵌入式控制系统。方法详细论述包装袋成型机的工作原理,通过送料、牵引、热封、分切等工序,将包装薄膜制成包装袋。给出硬件设计方法,包括控制器、传感器模块、电动执行模块等。同时讨论伺服电机升降速控制算法和张力浮动辊控制算法,基于u C/OS-II给出软件设计方法。结果该控制系统具有集成度高、实时性好、开发成本不高等优点。结论该控制系统能够满足包装袋成型机的工艺要求和控制需求。

基于ARM的四轴飞行器协调控制系统的设计

基于目前很流行的多轴飞行器,提出了一主多从多机协调控制系统。主机以ARM架构微处理器S3C6410为主控核心,采用Linux操作系统作为S3C6410软件开发平台。从机采用STM32为控制核心,多机间基于2.4G无线通讯模块进行信息交互。介绍了系统的总体设计、各节点间通信设计、主从机底层行为控制,并进行了相关测试,试验结果表明该系统能够满足多机协调控制的要求。

基于ARM协调控制的多路信号采集系统

数据采集是现代工控领域至关重要的一环,应用多处理器的主从控制模式可大大提高信号的采集与处理性能。32位ARM处理器进行信号的高速采集与处理,CAN总线建立的拓扑网络负责多个处理器间数据、命令的有效对接,利用uC/OS-Ⅲ实时系统实现信号采集与处理任务的调度,该模式可增进多个处理器间的协调控制,实现多路信号的采集和远程传输,还能增强系统的实时性和稳定性,同时可最大程度抑制线路传输干扰。

舰船编队雷达网协同体系中的嵌入式ARM仿真系统研究

舰船航行在广阔的海面时,其编队之间的通信系统会独立于岸基的通信系统,为了能够保证编队成员之间的通信安全,往往会通过雷达系统建立临时的协同通信网络,一方面加强了通信的距离,同时也能够有利于成员之间的信息共享,发挥编队的优势。本文主要研究舰船雷达协同作战系统的通信原理,然后简述系统作战的拓扑网络。结合最新的ARM嵌入式通信平台,对协同通信中遇到的数据处理、控制器数据过滤等技术进行验证,提出了一些有益的建议。

基于ARM及ZigBee的智能家居远程监控系统实现路径

以用户对智能家居远程监控系统的实际需求入手,根据用户的需求及其未来发展趋势,基于ZigBee技术和ARM处理器设计一款智能家居远程监控系统,进一步阐述该系统报警联动、视频监控、红外信号收发等模块功能及实现方法,以期达到智能化、网络化管理家居环境的目的,具有较好的推广和应用价值。

考虑制造误差的摆线轮减速器转臂轴承承载分析

摆线轮减速器转臂轴承的承载性能和磨损状况与减速器的回转精度和寿命有密切关系。针对某150BX型摆线轮减速器轴承孔实际磨损状况,首先,建立转臂轴承的承载模型,明确了最大载荷及其方向的变化规律;然后,建立含制造误差的摆线轮和曲柄轴的运动模型,分析制造误差对转臂轴承运动过程中的干涉情况,获得了转臂轴承上最大干涉位置和误差选配方法。研究为摆线轮减速器转臂轴承的磨损计算和关键零部件的误差选配提供了依据。

基于高增益观测器的火炮药协调臂位置控制

针对火炮协调输药机在协调过程中药协调臂运动到位精度不足的问题,提出了一种基于高增益观测器的火炮药协调臂自适应滑模控制策略,设计高增益观测器来估计火炮药协调臂伺服系统的未知状态并对其进行有效的在线跟踪和补偿,设计滑模控制器来消除所观测状态的误差,从而实现药协调臂机电伺服系统的快速高精度控制。针对滑模控制过程中出现的高频抖振现象,设计了一种自适应律并与滑模控制器相结合,从而极大地削弱了控制量的抖振。仿真实验结果表明,在输药机装满药的极端工况下,该控制策略能够大幅提高药协调臂的到位精度,具有较强的鲁棒性。

空间机动目标双臂协调柔顺操作控制方法

针对被操作目标运动状态变化导致双臂与目标间内力发生突变的问题,提出了一种空间机动目标双臂协调柔顺操作控制方法。首先,针对空间双臂协调柔顺操作任务,分别建立双臂空间机器人开链动力学模型和闭链动力学模型;其次,考虑目标机动产生的扰动,设计阻抗参数自主调整策略,在双臂末端与目标间作用力发生较大变化时,可以保证双臂协调操作任务的平稳性和安全性;最后,搭建双臂协调柔顺操作地面物理试验系统,并开展物理仿真试验验证,试验结果表明了本文所提方法的有效性。

坑道钻机用机械臂结构设计及运动学研究

为减少煤矿坑道钻机施工人员劳动强度,保障作业安全,设计了多自由度机械臂,分析了该机械臂的主要结构和工作原理,得到了各部件的基本运动参数,研究了抓手体的位姿、速度与各部件运动学参数之间的关系,利用Matlab软件仿真得到了抓手体的作业范围,同时对比研究了采用依次驱动和同步驱动方式下抓手体的运动轨迹。结果表明:采用同步驱动方式能够使抓手体的运行速度和加速度曲线更平滑,运行工况更趋于平稳,此时抓手体运动的速度和加速度最大值仅分别为347 mm/s、55 mm/s2,能够有效降低抓手体的速度和加速度峰值以及减少波动次数。研究结果为多自由度机械臂在坑道钻机的现场施工使用提供了理论基础。

基于单片机的直角坐标系按摩机器人设计

【目的】为了能提供多样化的按摩体验,并实现方便、快捷的效果,设计了基于单片机的直角坐标系按摩机器人。【方法】按摩机器人主要由机械臂、筋膜枪组成,将控制系统与单片机电路集成在一块控制板中,通过控制端或选择自动运行模式来控制按摩机器人的运行。【结果】通过控制板控制机械臂来带动筋膜枪运动,通过调节机械臂的力度和筋膜枪震动频率来实现放松肌肉和按摩等功能。【结论】基于单片机的直角坐标系按摩机器人设计对提高人们生活质量、促进健康产业的发展具有重要意义。

移动机械臂低自由度视觉搜寻与抵近策略

针对陌生环境下的目标搜索问题,提出了一种移动机械臂低自由度视觉搜寻与抵近策略。首先研究了两关节机械臂组合视野空间大小,基于两关节运动实现未知空间的目标粗搜索,获取目标物的粗略位置;然后根据几何关系推算机械臂两关节的后续运动角度,使目标物位于视野中心,实现精定位;最后采用车臂协同控制策略,控制机械臂抵近目标,并保证目标始终位于视野中心区域,得到更好的抵近精度。仿真结果表明,该方法使用二自由度即可实现目标的搜索与抵近,控制器设计简单,定位效率高,适合工程应用。

基于MATLAB与ADAMS的机械臂联合仿真研究

为提高机械臂设计效率,充分利用了虚拟仿真,搭建了机械臂的虚拟仿真系统。首先在Solidworks中建立了四关节机械臂的实体模型;然后将其导入动力学仿真软件Adams中,进行运动学及动力学仿真;最后通过Adams与Matlab的接口模块Adams/control,利用Matlab/Simulink模块搭建了机械臂的联合仿真控制系统,实现基于Matlab与Adams的机械臂的联合仿真。仿真结果表明机械臂系统具有较好的动态响应特性及较好的轨迹跟踪能力。

关节臂式柔性三坐标测量系统的数学模型及误差分析

关节臂式柔性三坐标测量系统是一种新颖的基于旋转关节和转动臂的三坐标测量系统,以角度测量基准取代了长度测量基准,它具有量程大、体积小、重量轻及使用灵活等优点．首先基于Denavit-Hartenberg方法建立了关节臂式柔性三坐标测量系统的理想数学模型和误差模型,并通过几何作图法对模型进行了验证.根据系统的特点和通过对系统中实际存在的影响测量结果的各种误差因素进行了详细分析,为进一步研究系统的误差补偿提供了理论基础．

保持基座稳定的双臂空间机器人轨迹规划研究

针对双臂空间机器人在轨执行任务中需要利用平衡臂稳定基座的问题,提出了两种典型应用需求—基座质心位置稳定、基座姿态和质心位置同时稳定的协调规划方法.首先,提出了"系统质心等效机械臂"的概念并推导其运动学模型,基于此模型的位置级反解规划平衡臂的运动轨迹,使基座质心位置稳定在期望位置;其次,根据角动量守恒定律确定反作用飞轮的运动速度,将飞轮与平衡臂的运动相结合,同时稳定基座姿态和质心位置;最后,建立双臂空间机器人系统的多体动力学模型并开展仿真研究.所提出的方法克服了以往基于微分运动学所无法回避的奇异问题,且不对平衡臂的质量特性和安装位置作特殊规定,仿真结果证明了方法的有效性.