Design of Robotic Visual Servo Control Based on Neural Network and Genetic Algorithm

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.

Learning-based force servoing control of a robot with vision in an unknown environment

A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of the robot are derived and learned by a neural network. Secondly, a learning controller based on the neural network is designed for the robot to trace the object. Thirdly, a discrete time impedance control law is obtained for the force servoing of the robot, the on-line learning algorithms for three neural networks are developed to adjust the impedance parameters of the robot in the unknown environment. Lastly, wiping experiments are carried out by using a 6 DOF industrial robot with a CCD camera and a force/torque sensor in its end effector, and the experimental results confirm the effecti veness of the approach.

Predictive Control for Visual Servo Stabilization of Nonholonomic Mobile Robots

活动机器人获得了的 nonholonomic 的视觉伺服稳定广泛的注意。当前，这个问题的解决方案不管多么不认为可见性限制和致动器是限制，因此设计控制器是困难的在实际申请认识到令人满意的性能。在这份报纸，为一个活动机器人的视觉伺服稳定的一个预兆的控制器被介绍。第一，利用产生速度的命令的一个运动学的预兆的稳定控制器被介绍。然后，来临以便 asymptotically 做活动机器人的实际速度到需要的，一个动态预兆的控制器被设计。建议预兆的控制器能容易处理限制。最后，几模拟被执行，并且结果说明建议控制计划是有效的解决视觉伺服稳定问题。

FORCE FEEDBACK MODEL OF ELECTRO-HYDRAULIC SERVO TELE-OPERATION ROBOT BASED ON VELOCITY CONTROL

The tele-operation robotic system which consists of an excavator as the construction robot, and two joysticks for operating the robot from a safe place are useful for performing restoration in damaged areas. In order to accomplish a precise task, the operator needs to feel a realistic sense of task force brought about from a feedback force between the fork glove of slave robot and unfamiliar environment. A novel force feedback model is proposed based on velocity control of cylinder to determine environment force acting on fork glove. Namely, the feedback force is formed by the error of displacement of joystick with velocity and driving force of piston, and the gain is calculated by the driving force and threshold of driving force of hydraulic cylinder. Moreover, the variable gain improved algorithm is developed to overcome the defect for grasping soft object. Experimental results for fork glove freedom of robotic system are provided to demonstrate the developed algorithm is available for grasping soft object.

Hand-eye-vision based control for an inspection robot's autonomous line grasping

In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.

Adaptive Stabilization for Uncertain Nonholonomic Dynamic Mobile Robots Based on Visual Servoing Feedback

nonholonomic 的稳定问题动态活动机器人与一修理(装天花板) 照相机在这份报纸被探讨。首先，一个照相机目标视觉 servoing 运动学的模型被利用针孔照相机模型介绍，一个运动学的稳定控制器为运动学的模型被给。然后，一个适应滑动模式控制器被设计面对与照相机系统联系的参量的无常稳定不明确的动态活动机器人。建议控制器不仅对象集体变化那样的结构化的无常而且到象骚乱那样的未组织的柔韧。建议控制系统的稳定性和估计的参数的固定被 Lyapunov 方法严厉地证明。模拟结果被介绍说明控制法律的表演。

A dual working mode mobile robot system based on visual guiding and visual servoing

A dual operational modes mobile robot system based on visual guiding and visual servo control is presented. This system consists of a mobile robot with a two-axis manipulator and a tele-operation station. In the visual guiding mode, for the robot works in an open loop visual servo control mode, the manipulating burden of the operator is reduced largely. In the visual servo mode the robot can locate the position of the target assigned by the operator and pick it up by its manipulator. With the help of the operator, the diffieuh problems of finding and handling a target in a complicated environment by the robot can be solved easily.

A Control Method for SMA Robotic Actuators

Soft robots show remarkable benefits over conventional rigid robots due to their high energy density and other factors. We propose a circular soft robot integrating the control system, actuating it with several shape memory alloy (SMA) actuators. Our research methodology involved connecting the DC voltage supply and L298N module to provide uninterrupted power to the actuator and thence control the actuator via Arduino Uno MCU and TOF camera. We designed the controller to simultaneously complete the positioning and manipulation tasks. A novel method utilizing visual servo and closed-loop control algorithm was proposed and integrated into the controller. This method involves the implementation of multi-gait locomotion using SMA actuators. Additionally, the development of closed-loop dynamic controllers for a continuous soft robot is also evaluated. The proposed control model is designed and simulated on the MATLAB tool. To verify the efficiency of the proposed forward-feedback controller, simulations and experiments were conducted in the current study. A new control method using PID control based on the Kalman filtering algorithm and visual servo for the SMA actuator designed in this research is introduced. We conclude that applying spike excitation voltage would benefit the actuating performance. Overall, the experimental results demonstrated a promising future for the purposed control method.

中国机器人伺服控制技术竞争力及提升路径

中国机器人核心技术竞争力与国际领先国家相比仍有很大的差距,迫切需要提升以伺服控制技术、减速机技术等为代表的机器人核心技术竞争力。文章采用专利信息数据从专利数量、专利质量、专利价值三个维度对中国机器人伺服控制领域的技术竞争力进行分析,并将其与美国、德国、韩国等领先国家进行比较,剖析中国机器人伺服控制技术发展过程中的优势与不足,最后从技术联合研发、聚焦关键技术、研发方向等方面提出了技术竞争力提升的路径。

工业机器人伺服电机控制方法研究

针对工业机器人中的伺服电机控制方法展开研究,旨在提高工业机器人的运动控制精度和稳定性。首先,分析了工业机器人中的伺服电机控制问题,指出传统PID控制方法存在的局限性;其次,提出了一种基于自适应PID算法的控制方法,并详细介绍了其数学原理和调整规则;最后,采用MATLAB/Simulink对所提方法进行了仿真实验,比较了标准PID方法和自适应PID方法在位置精度和速度响应时间上的表现。结果表明,自适应PID方法具有更高的控制精度和更快的响应速度。

电液伺服系统多PID控制器参数整定优化

为了解决挖掘机器人动臂、斗杆和铲斗不同电液伺服系统中多个比例–积分–微分(PID)控制器参数优化的难题,提高挖掘机器人铲斗齿尖轨迹跟踪精度,采用改进的粒子群算法(PSO)对多PID控制器参数进行整定优化.首先,建立电液伺服系统的数学机理模型,在理论模型的基础上,采用递推最小二乘辨识法(RLS)得到实际的机理模型.其次,提出一种改进的PSO算法,采用非线性自适应惯性权重、引入异步变化策略、设计精英变异方法.接着,搭建仿真验证平台,跟踪正弦轨迹,比较传统Z-N参数整定方法、基本PSO算法和改进PSO算法的差别.最后,以挖掘机器人最常见的整平为代表工况,基于23 t挖掘机器人实验平台进行实验验证.实验结果表明,改进PSO算法的跟踪精度最高,与基本PSO算法相比,明显提高了轨迹跟踪精度.

足式机器人腿部关节改进单神经网络PID控制算法研究

为了满足液压足式机器人在复杂环境中实现精确、快速的腿部关节控制需求,把单神经网络PID能够实时调节参数的优点运用到足式机器人液压机械腿关节的控制中,在单神经网络PID的基础上增加机械腿关节的位置和速度控制算法,形成改进单神经网络PID,实现了对神经元比例参数自调整、PID参数的自整定,能够较好地适应内、外参数的变化,增强了腿部关节的快速性、精确性。在Simulink中进行建模仿真以及在设计的以STM32为中央处理芯片的控制平台上进行实验测试,结果表明:改进单神经网络PID在足式液压机器人的腿部关节控制中具有响应速度快、超调量小、控制精度高、鲁棒性强等优点。

面向溺水救援机器人平稳跟踪的模糊比例微分控制视觉伺服方案

针对溺水救援机器人的平稳跟踪需求,提出一种基于模糊比例微分控制的视觉伺服方案,通过场馆顶部安装的俯视摄像头获取机器人的坐标位置,使用虚拟导航线设计动态行走路径,计算偏移方向、偏移角并制定转弯规则;利用三角隶属度函数制定模糊比例、微分控制规则表,根据2种规则表中的比例、微分系数分别控制机器人的偏移角、距离偏移量及其变化率,实现机器人的跟踪与避障的平稳性调整;机器人采用核相关滤波跟踪算法对溺水人员进行跟踪,在溺水人员位置变化时调整运动方向,依靠实时、稳定的声呐信息设置偏移角,实现避障功能;对所提出的方案在先锋P3DX型机器人上进行实验验证。结果表明:机器人能及时应对目标变化,没有跟错、跟丢现象;在不同工况时的横滚角均小于1°,避障率达到100%,能够快速、稳定、准确地到达目标位置,达到溺水救援机器人的前期应用要求。

基于语义分割网络的植保机器人视觉伺服控制方法

为实现稳定可靠的植保机器人视觉伺服控制,提出了一种基于语义分割网络的作物行特征检测方法。基于语义分割网络ESNet实现农田场景图像像素级带状区域检测,并利用最小二乘算法拟合得到每条行作物线特征;在此基础上通过设计一种主导航线提取算法获取导航路径,并利用卡尔曼滤波对主导航线几何参数进行平滑处理,有效抑制了不平整地面导致的机器人运动颠簸与视觉图像测量噪声引起的导航参数波动。继而构建机器人前轮转向、后轮差速的阿克曼运动学模型;在图像空间坐标下设计纯追踪控制器实现植保机器人的伺服运动控制。大田环境下的现场实验结果为:总体横向偏差为0.092 m,验证了本文方法的有效性。

基于ROS的蔬菜移栽机器人控制系统设计

为实现温室蔬菜移栽无人智能化作业,设计了基于ROS架构的蔬菜移栽机器人控制系统,实现了蔬菜移栽机器人自主取苗部件、秧苗栽植部件和自主移动平台的自动控制。控制系统主要分为总线单元和导航单元,并基于EtherCAT总线和Realsense深度相机搭建硬件系统,利用分层模块化理念开发基于ROS架构的软件控制系统,搭建并实现了移栽作业中取苗、投苗、栽苗及移动平台协同一体化控制。实验结果表明:在大于2s/株的取栽苗周期运动条件下,可实现较高成功率的移栽作业。所设计控制系统保证了移栽作业成功率,提高了当前蔬菜移栽机的智能化水平。

机器人核心零部件技术现状及趋势综述

机器人是制造业高质量发展的关键支撑装备,我国机器人及核心零部件已形成较为完善的产业体系,机器人用控制器综合性能指标接近国际先进水平,正向智能化、可扩展、高可靠方向引领行业发展。但在精密减速器、驱动器及伺服电机领域存在精度保持性不足、可靠性低、运行平稳性和批量一致性差等关键“卡脖子”问题,无法满足复杂高端领域应用需求。对工业机器人核心零部件技术现状及趋势进行综述,从精密减速器、控制器系统、伺服系统以及测评方法4个方面对近些年国内外研究成果和存在的问题展开讨论,分析国内机器人核心零部件的关键技术与国际先进水平的差距,找出发展痛点与根本原因,有利于在工业机器人核心零部件研制过程中实现关键技术突破。

基于ESO的分拣并联机器人无标定视觉伺服自适应滑模控制

针对无标定分拣并联机器人需获取精确图像雅可比矩阵的问题,同时为克服图像检测误差、建模误差及外部干扰对无标定视觉伺服系统的影响,提出一种基于扩张状态观测器(extended state observer,ESO)的分拣并联机器人无标定视觉伺服自适应滑模控制方法。通过将表征机器人图像空间与任务空间映射关系的图像雅可比矩阵与系统不确定项集总到同一通道的状态方程,引入ESO对分拣并联机器人视觉伺服系统的集总不确定性进行在线估计,设计一种基于扩张状态观测器的自适应积分滑模控制器,并通过设计自适应律动态调整滑模控制切换增益,以提高视觉伺服系统精度,同时达到抑制滑模控制抖振的效果。采用Lyapunov稳定性理论证明该控制方法的稳定性,最后通过仿真实验验证了所提出视觉伺服自适应滑模控制方法的可行性和有效性。

基于ROBONOVA2平台的舞蹈机器人设计与实现

基于ROBONOVA2平台推出了一款舞蹈机器人,通过Robobasic平台和图形化界面对机器人进行开发。结合了军旅文化主题,基于ROBONOVA2的舞蹈机器人设计并实现了一套舞蹈动作,并通过舵机控制,较好的提高了机器人的动作协调度与人机交互性。

纺织车间纱筒取装多自由度机械臂关节轨迹跟踪控制

纱筒取装换料是纺织车间里常用的一种作业,利用机械臂系统去实现纱筒换料,能够实现纺织车间作业效率的提升。在纱筒换料多自由度抓取机器人抓取纱筒放置到纱架的过程中,机器臂末端夹爪要精准抓取纱筒进行上下料,对机械臂要有精确,快速控制的需求,因此,研究关节机器人的运动轨迹的跟踪控制具有重要意义。为使得机器人在运动控制中精确定位,对纱筒夹取机械臂系统进行动力学建模得到相关力矩参数,对机械臂关节电机进行数学建模,并构建了机械臂的关节轨迹跟踪伺服控制系统,基于PID控制算法,利用MATLAB软件Simulink平台对五自由度机械臂模型进行轨迹跟踪可视化仿真实验,给定期望角度,通过PID控制算法的跟踪得到其实际输出角度,仿真实验结果表明PID控制算法跟踪轨迹误差小于0.08(rad),机械臂系统在0.02秒内快速响应,纱筒抓取五自由度机械臂系统在0.3秒内可达到系统稳态时间,能够使得机械臂末端夹爪对纱筒进行精确的抓取,满足了纺织车间对于纱筒上下料的作业需求,同时提高了其工作效率。

基于分布式PLC的罗拉柔性装配系统设计

针对罗拉装配生产中工件规格种类多、工序繁杂、流程长、中转环节多、以人工操作为主等特点,为提高企业的自动化程度,该文提出了基于Device Net总线的分布式PLC控制系统。对生产线中各单元进行模块化柔性设计,兼容多工件规格、多工序组合;应用工业机器人与伺服控制技术,实现了机器人自动上下料、自动清洗、激光打标、轴承压装、保护帽安装、注黄油、喷防锈油、裹膜包装、码垛装箱等连续流程作业。实际运行表明,该系统运行可靠、维护方便,能有效降低用工成本、提高生产效率,为企业实现连续化、自动化、信息化的全面智能升级改造提供了基础。