Seam tracking and visual control for robotic arc welding based on structured light stereovision

A real-time arc welding robot visual control system based on a local network with a multi-level hierarchy is developed in this paper. It consists of an intelligence and human-machine interface level, a motion planning level, a motion control level and a servo control level. The last three levels form a local real-time open robot controller, which realizes motion planning and motion control of a robot. A camera calibration method based on the relative movement of the end-effector connected to a robot is proposed and a method for tracking weld seam based on the structured light stereovision is provided. Combining the parameters of the cameras and laser plane, three groups of position values in Cartesian space are obtained for each feature point in a stripe projected on the weld seam. The accurate three-dimensional position of the edge points in the weld seam can be calculated from the obtained parameters with an information fusion algorithm. By calculating the weld seam parameter from position and image data, the movement parameters of the robot used for tracking can be determined. A swing welding experiment of type Ⅴgroove weld is successfully conducted, the results of which show that the system has high resolution seam tracking in real-time, and works stably and efficiently.     

Research on the controller of an arc welding process based on a PID neural network

A controller based on a PID neural network （PIDNN） is proposed for an arc welding power source whose output characteristic in responding to a given value is quickly and intelligently controlled in the welding process. The new method syncretizes the PID control strategy and neural network to control the welding process intelligently, so it has the merit of PID control rules and the trait of better information disposal ability of the neural network. The results of simulation show that the controller has the properties of quick response, low overshoot, quick convergence and good stable accuracy, which meet the requirements for control of the welding process.     

模糊神经网络PID控制在焊缝跟踪中的应用

1 Introduction Real- time seam tracking is the key step for welding automation. Because welding itself is a complex process, the factors that affect the welding have uncertainty and non - linear characters. Therefore, classical control in seam tracking cannot carry a satisfying result. In latter- day, Fuzzy mathematic and Neural Network appearance, being used on uncertain nonlinear system, and have a good effect. The hybrid controller, which combines Fuzzy con- trol and PID control, uses F…     

PD-based trajectory tracking control in automatic cell injection system

Trajectory tracking technology has been the focus of industrial manipulatory applications for many years, and its research has been found in micromanipulation in bioengineering recently. In this paper, a hybrid vision and force control method is applied to the automatic cell injection. The three-dimensional cell injection process involves the trajectory tracking in free space and the force control in contact space. A PD plus feedforward compensation control method is applied to the trajectory tracking in 3D space. Further, a PD-based robust controller is introduced into trajectory tracking while the systemic uncertainty of the cell injection is additionally considered. Both of the two control methods are theoretically proved to be exponential convergent. Finally, the effectiveness of the proposed method is verified as compared with other control methods by its application to trajectory tracking problem.     

Adaptive tracking control for uncertain dynamic nonholonomic mobile robots based on visual servoing

The trajectory tracking control problem of dynamic nonholonomic wheeled mobile robots is considered via visual servoing feedback. A kinematic controller is firstly presented for the kinematic model, and then, an adaptive sliding mode controller is designed for the uncertain dynamic model in the presence of parametric uncertainties associated with the camera system. The proposed controller is robust not only to structured uncertainties such as mass variation but also to unstructured one such as disturbances. The asymptotic convergence of tracking errors to equilibrium point is rigorously proved by the Lyapunov method. Simulation results are provided to illustrate the performance of the control law.     

Visual Object Tracking and Servoing Control of a Nano-Scale Quadrotor: System,Algorithms, and Experiments

There are two main trends in the development of unmanned aerial vehicle(UAV)technologies:miniaturization and intellectualization,in which realizing object tracking capabilities for a nano-scale UAV is one of the most challenging problems.In this paper,we present a visual object tracking and servoing control system utilizing a tailor-made 38 g nano-scale quadrotor.A lightweight visual module is integrated to enable object tracking capabilities,and a micro positioning deck is mounted to provide accurate pose estimation.In order to be robust against object appearance variations,a novel object tracking algorithm,denoted by RMCTer,is proposed,which integrates a powerful short-term tracking module and an efficient long-term processing module.In particular,the long-term processing module can provide additional object information and modify the short-term tracking model in a timely manner.Furthermore,a positionbased visual servoing control method is proposed for the quadrotor,where an adaptive tracking controller is designed by leveraging backstepping and adaptive techniques.Stable and accurate object tracking is achieved even under disturbances.Experimental results are presented to demonstrate the high accuracy and stability of the whole tracking system.     

Adaptive control of permanent magnet synchronous machines with disturbance estimation

In this paper,an adaptive control scheme is introduced for permanent magnet synchronous machines (PMSMs)as an alternative to classical control techniques.The adaptive control strategy capitalizes on the machine’s inverse dynamics to achieve accurate tracking by using an observer to approximate disturbance in the form of friction and load torque.The controller’s output is then fed to a space vector pulse width modulation(SVPWM)algorithm to produce duty cycles for the inverter.The control scheme is validated through a set of simulations on an experimentally validated PMSM model.Results for different situations highlight its high speed tracking accuracy and high performance in compensating for friction and load disturbances of various magnitudes.     

Autonomous Control Strategy of a Swarm System Under Attack Based on Projected View and Light Transmittance

In the study of a visual projection field with swarm movements,an autonomous control strategy is presented in this paper for a swarm system under attack.To ensure a fast swarm dynamic response and stable spatial cohesion in a complex environment,a new hybrid swarm motion model is proposed by introducing global visual projection information to a traditional local interaction mechanism.In the face of attackers,individuals move towards the largest free space according to the projected view of the environment,rather than directly in the opposite direction of the attacker.Moreover,swarm individuals can certainly regroup without dispersion after the attacker leaves.On the other hand,the light transmittance of each individual is defined based on global visual projection information to represent its spatial freedom and relative position in the swarm.Then,an autonomous control strategy with adaptive parameters is proposed according to light transmittance to guide the movement of swarm individuals.The simulation results demonstrate in detail how individuals can avoid attackers safely and reconstruct ordered states of swarm motion.     

Dynamics and control of a novel 3-DOF parallel manipulator with actuation redundancy

This paper deals with the dynamics and control of a novel 3-degrees-of-freedom （DOF） parallel manipulator with actuation redundancy. According to the kinematics of the redundant manipulator, the inverse dynamic equation is formulated in the task space by using the Lagrangian formalism, and the driving force is optimized by utilizing the minimal 2-norm method. Based on the dynamic model, a synchronized sliding mode control scheme based on contour error is proposed to implement accurate motion tracking control. Additionally, an adaptive method is introduced to approximate the lumped uncertainty of the system and provide a chattering-free control. The simulation results indicate the effectiveness of the proposed approaches and demonstrate the satisfactory tracking performance compared to the conventional controller in the presence of the parameter uncertainties and un-modelled dynamics for the motion control of manipulators.     

基于颜色和特征匹配的视频图像人脸检测实现技术

A face detection method using statistical skin-color model and facial feature matching is presented in this paper.According to skin-color distribution in YUV color space,we develope a statistical skin-color model through interactive sample training and learning.Using this method we convert the color image to binary image and then segment face-candidate regions in the video images.In order to improve the quality of binary image and remove unwanted noises,filtering and mathematical morphology are empolied.After these two processing,we use facial feature matching for further detection.The presence or absence of a face in each region is verified by means of mouth detector based on a template matching method.The experimental results show the proposed method has the features of high speed and high efficiency,but also robust to face variation to some extent.So it is suitable to be applied to real-time face detection and tracking in video sequences.     

卡尔曼滤波焊缝跟踪控制

在视觉传感的电弧自动焊接过程中,需要根据视觉信息来控制电弧准确地跟踪焊缝.由于强烈的弧光干扰,使得从焊接区图像中直接提取电弧与焊缝的偏差信息十分困难.为此提出一种利用熔池图像质心和卡尔曼滤波来间接获取电弧与焊缝偏差的方法.选择熔池图像质心作为状态向量,建立基于图像质心的状态方程和焊缝位置测量方程.利用卡尔曼滤波消除过程噪声和测量噪声的影响,通过对熔池图像质心的状态估计,准确获取焊缝位置以及电弧与焊缝之间的偏差量,为自动焊接过程的焊缝跟踪控制提供准确信息.焊接试验结果表明,利用卡尔曼滤波方法可有效降低过程噪声和测量噪声的影响,从而提高焊缝跟踪控制精度.     

Autonomous Detection of Weld Seam Profiles via a Model of Saliency-Based Visual Attention for Robotic Arc Welding

This paper presents a method of autonomously detecting weld seam profiles from molten pool background in metal active gas (MAG) arc welding using a novel model of saliency-based visual attention. First, a vision sensor based on structured light is employed to capture laser stripes and molten pools simultaneously in the same frame. Second, to effectively detect the weld seam profile from molten pool background for next autonomous guidance of initial welding positions and seam tracking, a model of visual attention based on saliency is proposed. With respect to the enhanced effect of saliency, the proposed model is much better than the classic models in the field. According to the comprehensive saliency map created by the proposed model, the weld seam profile can be extracted after threshold segmentation and clustering are applied to it in turn. Third, different weld seam images are used to demonstrate the robustness of the proposed methodology and last, to evaluate the performance of the proposed method, a measure called profile extraction rate (PER) is computed, which shows that the extracted weld seam profile can basically meet the requirements of seam tracking and the guidance of welding torches.     

经济型焊缝跟踪视觉传感器的研制

利用普通的焊接护目镜玻璃制作了熔池图像视觉传感器,在304#不锈钢等离子弧焊缝跟踪试验中获得的图像是足够清晰的,能够清楚地看到接缝和焊接熔池.在工厂车间里进行的试验证明:这种低成本的视觉传感器可以用于304#不锈钢的等离子弧焊接过程的实时焊缝跟踪和控制.     

基于视觉与电弧多信息传感的焊缝跟踪算法

随着焊接传感技术以及信号处理技术的快速发展,人们越来越注重对焊接过程质量控制的研究,而多传感器信息融合技术是焊接质量控制的一种重要的方法,采用该技术实现熔化极气体保护焊(MIG)脉冲焊接质量的自动控制。该技术采用了视觉传感器和电弧传感器将采集的不同的描述信息进行了有效的特征提取和传输,并运用多传感器信息融合算法进行焊缝的跟踪。视觉传感器利用工业电荷耦合元件(CCD)获取图像信息控制焊炬的横向偏差信息,电弧传感器利用数据采集卡获取电流信息控制焊炬的高度互补偏差信息和横向的冗余信息,将两种传感器得到的冗余信息和互补信息在特征层下进行融合实现焊接过程横向和高度的纠偏控制。冗余信息的融合可以实现视觉传感的图像去噪,而互补信息的融合可以进一步提高焊缝跟踪的精度。实验结果表明,所提算法能够较好地提高焊接的质量,从而也验证了算法的有效性和合理性。     

Research on the Real-time Tracking Information of Three-dimension Welding Seam in Robotic GTAW Process Based on Composite Sensor Technology

Aiming at the shortcomings of teaching-playback robot that can??t track the three-dimensional welding seam in real time during GTAW process, this paper designed a set of composite sensor system for tracking the three-dimensional welding seam based on visual sensor and arc sensor technology, which can effectively acquire three-dimensional welding seam information, such as clear images of seam and pool and stable arc voltage signals. The characteristic values of weld image and arc voltage signals were accurately extracted by using proper processing algorithm, and the experiments have been done to verify the precision of processing algorithms. The results demonstrate that the error is very small, which is accurate enough to meet the requirements of the subsequent real-time tracking and controlling during the welding robot GTAW process.     

基于图像处理的模糊控制埋弧焊缝跟踪研究

焊接工艺由于其本身加工过程及环境的复杂性,使得焊缝难以精确跟踪.针对埋弧焊系统,采用视觉传感器进行焊缝跟踪,得到误差信号后,使用分段拼接控制的方法,使误差快速收敛,且减小超调.首先对焊缝图像进行预处理,使用自动化的阈值进行分割得到焊缝区域,应用边缘检测和Hough变换得到焊缝边缘,计算得到焊缝中心位置、焊矩和焊缝偏差;然后采用模糊增量式分段PI控制处理误差,当误差较大时采用增量式PI控制消除误差,当误差较小时应用模糊控制,设计了隶属度表以及模糊推理机制,采用小误差的模糊控制有效地抑制了超调,使误差快速收敛.最终仿真结果显示,使用PI混合模糊控制后,超调量被控制在0.2个单位以内,调节时间小于1 s,基本实现了对焊缝的快速准确跟踪.     

Weld seam profile detection and feature point extraction for multi-pass route planning based on visual attention model

Automatic multi-pass route planning is one of key technologies for thick plate in robotic metal active gas (MAG) arc welding. In this research, a scheme for the extracting feature points of the weld seam profile to implement automatic multi-pass route planning, and guidance of the initial welding position in each layer during MAG arc welding, is presented. It consists of two steps: first a vision sensor based on structured light is employed to capture laser stripes and molten pools simultaneously within the same frame, and the laser stripe, forming the weld seam profile is detected by a visual attention model based on saliency. Then a methodology of polynomial fitting plus derivatives for feature point extraction of the weld seam profile is suggested. With respect to the effectiveness of highlighting the laser stripe, the proposed model is much better than the classic ones in this field, whereas the feature point extraction methodology in this paper outperforms typical template matching. Finally, the performance of the proposed scheme is demonstrated on different weld seam images captured in different layers and different welding experiments.     

线阵CCD传感器埋弧焊自动跟踪系统

针对埋弧焊自动跟踪系统,采用线阵CCD接收散射光信号的光路结构,有效地减小了工件表面状况对传感器检测信号的干扰,着重介绍了埋弧焊自动跟踪系统的主要组成以及工作原理。利用线阵CCD传感技术,用把焊缝信息采集至计算机中并进行识别的方法,设计了焊缝跟踪算法程序以及驱动执行跟踪的步进电机的程序,通过微机系统的监控。实现了埋弧焊的自动跟踪功能。现场实验表明,该系统跟踪精度较高、具有广阔的应用前景。     

Real-Time Seam Tracking Technology of Welding Robot with Visual Sensing

A seam tracking system with visual sensing free from calibration was developed for the robot applied in gas tungsten arc welding. A visual sensor with double-layer filter system was researched for the different levels of the welding current. An image processing in C+?+ language was developed to extract the seam trajectory and the offset of the torch to the seam in the welding images of aluminum alloys plates with grooves. The rectifying rule of the robot used in this paper was found based on the experimental data, and the seam tracking controller was also analyzed and constructed. The experimental results on straight line seam and curve seam demonstrated the efficiency of the proposal seam tracking system.