空间连续型机器人自适应鲁棒容错控制

针对空间连续型机器人系统三臂节执行器并发故障的问题,提出一种自适应鲁棒容错控制算法.采用非奇异快速终端滑模控制器,并通过自适应RBF(Radial Basis Function)神经网络在线调整控制器的切换项增益,使控制器在模型参数摄动和外部干扰下依旧具有较高的跟踪精度和较强的鲁棒性.基于Lyapunov稳定性理论,证...     

机器人圆形焊缝三维定位方法

自动化寻迹焊接过程中有许多焊缝为圆形,在焊缝特征点的坐标确定以后如何确定圆形焊缝的中心轨迹线是至关重要的.利用空间解析几何的原理,结合最小二乘法,既利用焊缝的已知信息又利用了实时监测点的信息,给出了圆形焊缝三维空间中心位置的确定方法.实验表明,该方法具有较高的精度和较强的实用性.     

Dietary Nutritional Information Autonomous Perception Method Based on Machine Vision in Smart Homes

In order to automatically perceive the user’s dietary nutritional information in the smart home environment, this paper proposes a dietary nutritional information autonomous perception method based on machine vision in smart homes. Firstly, we proposed a food-recognition algorithm based on YOLOv5 to monitor the user’s dietary intake using the social robot. Secondly, in order to obtain the nutritional composition of the user’s dietary intake, we calibrated the weight of food ingredients and designed the method for the calculation of food nutritional composition; then, we proposed a dietary nutritional information autonomous perception method based on machine vision (DNPM) that supports the quantitative analysis of nutritional composition. Finally, the proposed algorithm was tested on the self-expanded dataset CFNet-34 based on the Chinese food dataset ChineseFoodNet. The test results show that the average recognition accuracy of the food-recognition algorithm based on YOLOv5 is 89.7%, showing good accuracy and robustness. According to the performance test results of the dietary nutritional information autonomous perception system in smart homes, the average nutritional composition perception accuracy of the system was 90.1%, the response time was less than 6 ms, and the speed was higher than 18 fps, showing excellent robustness and nutritional composition perception performance.     

全柔性空间机器人运动振动一体化输入受限重复学习控制

探究基座、臂、关节全柔性影响下空间机器人动力学模拟、运动控制及基座、臂、关节三重柔性振动主动抑制的问题,设计了不基于系统模型信息的运动振动一体化输入受限重复学习控制算法.将柔性基座与关节等效为线性弹簧与扭转弹簧,柔性臂视为欧拉-伯努利梁模型,利用拉格朗日方程与假设模态法建立动力学模型,然后,用奇异摄动理论将模型分解为包含刚性变量与臂柔性振动的慢变子系统,包含基座、关节柔性振动的快变子系统,并分别设计相应的子控制器,构成了带关节柔性补偿的一体化控制算法.针对慢变子系统,提出输入受限重复学习控制算法,由双曲正切函数,饱和函数与重复学习项构成,双曲正切函数与饱和函数实现输入力矩受限要求,重复学习项补偿周期性系统误差,以完成对基座姿态、关节铰周期轨迹的渐进稳定追踪.然而,为了同时抑制慢变子系统臂的柔性振动,运用虚拟力的概念,构造同时反映臂柔性振动与系统刚性运动的混合轨迹,提出了基于虚拟力概念的输入受限重复学习控制器,保证基座、关节轨迹精确追踪的同时,对臂的柔性振动主动抑制.针对快变子系统,采用线性二次最优控制算法抑制基座与关节的柔性振动.仿真结果表明:控制器适用于一般柔性非线性系统,满足输入力...     

基于电磁超声的天然气管道机器人测控系统设计

分析了国内天然气管道现状及检测维护情况,针对目前天然气管道裂纹缺陷检测问题,采用电磁超声检测方法,并结合虚拟仪器技术,设计了天然气管道机器人测控系统。系统以PXI模块化仪器平台为核心,结合数据采集模块和运动控制模块构建了硬件平台,以LabVIEW编程语言为基础开发了人机交互软件平台。该系统能够控制机器人在管道内的运动,并可在管道内壁激励和接收超声导波。整个系统可靠性高、扩展性强、人机交互界面友好,满足了机器人管内电磁超声检测作业时的运动控制、数据采集及处理要求。     

带滑移铰空间机器人运动规划的混合优化策略

研究了自由漂浮带滑移铰空间机器人非完整运动规划的最优控制问题,提出一种由高斯伪谱法求解可行解与直接打靶法求解最优解相结合的混合优化策略.首先,根据多体系统动力学理论建立空间机器人的动力学模型,给定系统的初始和目标位形,将空间机器人运动规划问题描述成博尔察（Bolza）型最优控制问题;然后,利用高斯伪谱法将最优控制问题离散为非线性规划问题,求解在较少勒让德-高斯（Legendre-Gauss,LG）点时状态变量和控制变量对应的可行解;最后,在LG点处离散控制变量,作为直接打靶法的初值,利用序列二次规划算法求解空间机器人系统的优化运动轨迹和最优控制输入.通过数值仿真,系统优化运动轨迹光滑平稳,最优控制输入也能很好地满足各种约束条件,仿真结果验证了该混合优化策略的鲁棒性和有效性.     

抛投式机器人高过载弹射泡沫塑料的共振吸能特性

针对抛投式机器人弹射过程中存在的高过载问题,使用缓冲材料对机器人进行减过载处理。讨论了缓冲材料在高过载情况下的吸能特性,根据抛投式机器人缓冲保护壳的结构和缓冲材料的性质,建立了单自由度支座激励系统数学模型,并对其系统固有频率和放大系数进行了分析。利用弹射器内弹道加速度测量系统测量了弹射器的激励曲线和机器人在缓冲材料作用下的响应。实验结果表明,当缓冲系统的固有频率与弹射器的激励频率接近时,系统产生共振,机器人所受过载增加。通过调整缓冲系统的参数,改变其固有频率,使系统放大系数小于1,避免产生共振。

     

Optimal Force Generation for an Underconstrained Planar Cable Robot

This paper presents a planar, underconstrained cable robot designed to operate on the vertical face of overhead roadway signs. The cables that actuate the robot extend over a set of rotatable pulley arms mounted at the top corners of the sign. The redundant degrees of freedom due to the pulley arms allow for improved force generation ability of the robot at all desired locations on the sign. Redundancy is resolved by optimizing the anisotropic force generated in a desired direction. There are four distinct solution regimes dependent on the desired force angle. Of the four solution regimes, two are constraint-bound solutions for each cable force and the complementary cable angle based on monotonicity analysis. The two additional solutions are constraint-bound in the cable angles resulting in a fixed geometry, and the well-known attainable force set solution is applied.     

Development of a semi-autonomous directional and spectroscopic radiation detection mobile platform

This paper presents a method for a small, inexpensive mobile robot equipped with a single high resolution scintillation detector to quickly survey an area and convey information about local sources of gamma radiation to a remote human operator. This is achieved by surrounding the detector with a lead sheath that blocks all gamma-rays except those incident along the detector's axial direction. A 180° horizontal scan is performed by rotating the detector and a directional profile of gamma radiation is constructed. In addition, a 180° visual panorama of the local area is assembled using a camera mounted on the detector. A plot of the detector count rate versus angle is then overlaid on top of the visual panorama and visible peaks clearly indicate the direction of local gamma radiation sources. Measuring the energy spectrum of gamma-rays in each direction produces a 2D count frequency histogram where distinct peaks indicate the energy and direction of local gamma-ray sources allowing the identification of different radio-isotopes. The mobile robot can use the peaks as goal directions and autonomously move towards gamma-ray sources.     

基于视觉测量与神经网络的工业机器人位姿补偿

为提高六轴工业机器人的绝对定位精度，本文提出了一种利用视觉测量数据通过ELM(Extreme Learning Machine)神经网络实现机器人位姿补偿的新方法．利用固定在机器人末端的手眼相机获取机器人的末端位姿，并借助ELM实现机器人末端执行器从目标位姿到预测指令位姿之间映射，用修正转角代替原转角使机器人末端执行器运行至修正位姿，实现补偿．特别的是，对于使用的ELM，以网络预测均方误差为指标定量选取了网络的最佳参数．相比之前的方法，本文提出的算法具有能够同时高精度补偿姿态角及位置误差的显著优点．为验证该位姿误差补偿方法的有效性，本文进行了实验验证．结果表明，相比较于未补偿前的机器人末端位姿误差，经该方法补偿后的位姿误差被稳定控制在较低水平，平均位置误差降低89.1 %；平均姿态角误差降低96.8 %．除此以外，位置误差与姿态角误差的标准差也分别降低了85.66 %和93.24 %．