A novel XY-Theta precision table and a geometric procedure for its kinematic calibration

Spatial precision positioning devices are often based on parallel robots, but when it comes to planar positioning, the well-known serial architecture is virtually the only solution available to industry. Problems with parallel robots are that most are coupled, more difficult to control than serial robots, and have a small workspace. In this paper, new parallel robot is proposed, which can deliver accurate movements, is partially decoupled and has a relatively large workspace. The novelty of this parallel robot lies in its ability to achieve the decoupled state by employing legs of a different kinematic structure. The robot repeatability is evaluated using a CMM and so are the actual lead errors of its actuators. A simple geometric method is proposed for directly identifying the actual base and mobile reference frames, two actuator's offsets and one distance parameter, using a measurement arm from FARO Technologies. While this method is certainly not the most efficient one, it yields a satisfactory improvement of the robot accuracy without the need for any background in robot calibration. An experimental validation shows that the position accuracy achieved after calibration is better than 0.339 mm within a workspace of approximately 150 mm×200 mm.     

Kinematic analysis and error modeling of TAU parallel robot

The TAU robot presents a new configuration of parallel robots with three degrees of freedom. This robotic configuration is well adapted to perform with a high precision and high stiffness within a large working range compared with a serial robot. It has the advantages of both parallel robots and serial robots. In this paper, the kinematic modeling and error modeling are established with all errors considered using Jacobian matrix method for the robot. Meanwhile, a very effective Jacobian approximation method is introduced to calculate the forward kinematic problem instead of Newton–Raphson method. It denotes that a closed form solution can be obtained instead of a numerical solution. A full size Jacobian matrix is used in carrying out error analysis, error budget, and model parameter estimation and identification. Simulation results indicate that both Jacobian matrix and Jacobian approximation method are correct and with a level of accuracy of micron meters. ADAMS's simulation results are used in verifying the established models.     

Kinematic calibration for collaborative robots on a mobile platform using motion capture system

For modern robotic applications that go beyond the typical industrial environment, absolute accuracy is one of the key properties that make this possible. There are several approaches in the literature to improve robot accuracy for a typical industrial robot mounted on a fixed frame. In contrast, there is no method to improve robot accuracy when the robot is mounted on a mobile base, which is typical for collaborative robots. Therefore, in this work, we proposed and analyzed two approaches to improve the absolute accuracy of the robot mounted on a mobile platform using an optical measurement system. The first approach is based on geometric operations used to calculate the rotation axes of each joint. This approach identifies all rotational axes, which allows the calculation of the Denavit–Hartenberg (DH) parameters and thus the complete kinematic model, including the position and orientation errors of the robot end-effector and the robot base. The second approach to parameter estimation is based on optimization using a set of joint positions and end-effector poses to find the optimal DH parameters. Since the robot is mounted on a mobile base that is not fixed, an optical measurement system was used to dynamically and simultaneously measure the position of the robot base and the end-effector. The performance of the two proposed methods was analyzed and validated on a 7-DoF Franka Emika Panda robot mounted on a mobile platform PAL Tiago-base. The results show a significant improvement in absolute accuracy for both proposed approaches. By using the proposed approach with the optical measurement system, we can easily automate the estimation of robot kinematic parameters with the aim of improving absolute accuracy, especially in applications that require high positioning accuracy.     

Vision-based Control of a Delta Parallel Robot via Linear Camera-Space Manipulation

One of the open problems to control a parallel robot in real-time is the larger number of parameters to be incorporated in the control model when compared to serial robots. This paper presents an innovative vision-based method to control a delta-type parallel robot based on Linear Camera-Space Manipulation. The proposed method is a simple and robust technique capable of achieving real-time control of robots without relying on the calibration of either the robot or the environment parameters. To document the robustness of this technique, a sensitivity analysis was performed in simulation where the effect of two sources of error on the end-point positioning are considered. Such sources are the variability of each link’s parameters, and the uncertainty of the visual measurements. Experimental results on a Clavel’s delta parallel robot show that end-point positioning errors obtained with Linear Camera-Space Manipulation are less than 1.5 mm, demonstrating a low sensitivity to parameter uncertainty in qualitative agreement with the simulation results. The results show that the developed approach is advantageous to control parallel robots for industrial applications in real-time and can obviate to a number of open problems common with the control of parallel robots.     

An Overview of Calibration Technology of Industrial Robots

With the continuous improvement of automation, industrial robots have become an indispensable part of automated production lines. They are widely used in a number of industrial production activities, such as spraying, welding, handling, etc., and have a great role in these sectors. Recently, the robotic technology is developing towards high precision, high intelligence. Robot calibration technology has a great significance to improve the accuracy of robot. However, it has much work to be done in the identification of robot parameters. The parameter identification work of existing serial and parallel robots is introduced. On the one hand, it summarizes the methods for parameter calibration and discusses their advantages and disadvantages. On the other hand, the application of parameter identification is introduced. This overview has a great reference value for robot manufacturers to choose proper identification method, points further research areas for researchers. Finally, this paper analyzes the existing problems in robot calibration, which may be worth researching in the future.      

A two-step method for kinematic parameters calibration based on complete pose measurement—Verification on a heavy-duty robot

The poor pose accuracy of industrial robots restricts their further application in aviation manufacturing. Kinematic calibration based on position errors is a traditional method to improve robot accuracy. However, due to the difference between length errors and angle errors in the order of magnitude, it is difficult to accurately calibrate these geometric parameters together. In this paper, a two-step method for robot kinematic parameters calibration and a novel method for position and orientation measurement are proposed and combined to identify these two kinds of errors respectively. The redundant parameter errors that affect the identification are also analyzed and eliminated to further improve the accuracy of this two-step method. Taking the Levenberg-Marquardt algorithm as the underlying algorithm, simulation results indicate that the proposed two-step calibration method has faster iteration speed and higher identification accuracy than the traditional one. On this basis, the calibration and measurement methods proposed in this paper are verified on a heavy-duty robot used for fiber placement. Experimental results show that the mean absolute position error decreases from 0.9906 mm to 0.3703 mm after calibration by the proposed two-step calibration method with redundancy elimination. The absolute position accuracy has increased by 41.81% compared with the traditional method based on position errors only and 14.97% compared with the two-step calibration method without redundancy elimination. At the same time, the orientation errors after calibration are not more than 0.1485°, and the average of absolute errors is 0.0447.     

基于目标检测的机器人手眼标定方法

智能协作机器人依赖视觉系统感知未知环境中的动态工作空间定位目标,实现机械臂对目标对象的自主抓取回收作业。RGB-D相机可采集场景中的彩色图和深度图,获取视野内任意目标三维点云,辅助智能协作机器人感知周围环境。为获取抓取机器人与RGB-D相机坐标系之间的转换关系,提出基于yolov3目标检测神经网络的机器人手眼标定方法。将3D打印球作为标靶球夹持在机械手末端,使用改进的yolov3目标检测神经网络实时定位标定球的球心,计算机械手末端中心在相机坐标系下的3D位置,同时运用奇异值分解方法求解机器人与相机坐标系转换矩阵的最小二乘解。在6自由度UR5机械臂和Intel RealSense D415深度相机上的实验结果表明,该标定方法无需辅助设备,转换后的空间点位置误差在2 mm以内,能较好满足一般视觉伺服智能机器人的抓取作业要求。     

多移动机器人合作系统中的单机控制体系结构研究

随着机器人技术的不断发展,出现了合作多移动机器人系统这一新的研究和应用领域,随之而来的是对机器人控制体系的新的要求．本文分析了合作多移动机器人系统对单机控制体系结构的要求,并以此为背景,在比较两种典型的智能机器人体系结构的基础上,提出一种混合分层的体系结构     

Estimation model for kinematic calibration of manipulators with a parallel structure

This article provides an estimation model for calibrating the kinematics of manipulators with a parallel geometrical structure. Parameter estimation for serial link manipulators is well developed, but fail for most structures with parallel actuators, because the forward kinematics is usually not analytically available for these. We extend parameter estimation to such parallel structures by developing an estimation method where errors in kinematical parameters are linearly related to errors in the tool pose, expressed through the inverse kinematics, which is usually well known. The method is based on the work done to calibrate the MultiCraft robot. This robot has five linear actuators built in parallel around a passive serial arm, thus making up a two-layered parallel-serial manipulator, and the unique MultiCraft construction is reviewed. Due to the passive serial arm, for this robot conventional serial calibration must be combined with estimation of the parameters in the parallel actuator structure. The developed kinematic calibration method is verified through simulations with realistic data and real robot kinematics, taking the MultiCraft manipulator as the case. © 1994 John Wiley & Sons, Inc.     

An active hybrid parallel robot for minimally invasive surgery

During the last years, there has been an increase in research in the field of medical robots. This trend motivated the development of a new robotics field called “robotic-assisted minimally invasive surgery”. The paper presents the kinematic and dynamic behavior of a parallel hybrid surgical robot PARASURG-9M. The robot consists of two subsystems: a surgical robotic arm, PARASURG 5M with five motors, and an active robotized surgical instrument PARASIM with four motors. The methodology for the robot kinematics is presented and the algorithm for robot workspace generation is described. PARASURG-9M inverse dynamic simulation is performed using MSC Adams and finally some numerical and simulation results of the developed experimental model with its system control are also described.     

基于虚拟现实技术的移动机器人视觉伺服控制系统设计

为了有效确保移动机器人视觉伺服控制效果,提高移动机器人视觉伺服控制精度,设计了基于虚拟现实技术的移动机器人视觉伺服控制系统。通过三维视觉传感器和立体显示器等虚拟环境的I/O设备、位姿传感器、视觉图像处理器以及伺服控制器元件,完成系统硬件设计。从运动学和动力学两个方面,搭建移动机器人数学模型,利用标定的视觉相机,生成移动机器人实时视觉图像,通过图像滤波、畸变校正等步骤,完成图像的预处理。利用视觉图像,构建移动机器人虚拟移动环境。在虚拟现实技术下,通过目标定位、路线生成、碰撞检测、路线调整等步骤,规划移动机器人行动路线,通过控制量的计算,实现视觉伺服控制功能。系统测试结果表明,所设计控制系统的位置控制误差较小,姿态角和移动速度控制误差仅为0.05°和0.12m/s,移动机器人碰撞次数较少,具有较好的移动机器人视觉伺服控制效果,能够有效提高移动机器人视觉伺服控制精度。     

A parallel processing architecture for sensor-based control of intelligent mobile robots

Parallel processing plays an important role in sensor-based control of intelligent mobile robots. This paper describes the design and implementation of a parallel processing architecture used for real-time, sensor-based control of mobile robots. This architecture takes the form of a network of sensing and control nodes, based on a novel module that we call Locally Intelligent Control Agent (LICA). It is a hybrid control architecture containing low-level feedback control loops and high-level decision making components. All the sensing, planning, and control tasks for intelligent control of a mobile robot are distributed across such a network, and operate in parallel. It has been used successfully in many experiments to perform planning and navigation tasks in real-time. Such a generic architecture can be readily applied to many diverse applications.     

Experimental kinematic calibration of parallel manipulators using a relative position error measurement system

Because of errors in the geometric parameters of parallel robots, it is necessary to calibrate them to improve the positioning accuracy for accurate task performance. Traditionally, to perform system calibration, one needs to measure a number of robot poses using an external measuring device. However, this process is often time-consuming, expensive and difficult for robot on-line calibration. In this paper, a methodical way of calibration of parallel robots is introduced. This method is performable only by measuring joint variable vector and positioning differences relative to a constant position in some sets of configurations that the desired positions in each set are fixed, but the moving platform orientations are different. In this method, measurements are relative, so it can be performed by using a simple measurement device. Simulations and experimental studies on a Hexaglide parallel robot built in the Sharif University of Technology reveal the convenience and effectiveness of the proposed robot calibration method for parallel robots.     

An accurate and robust visual-compass algorithm for robot-mounted omnidirectional cameras

Due to their wide field of view, omnidirectional cameras are becoming ubiquitous in many mobile robotic applications.  A challenging problem consists of using these sensors, mounted on mobile robotic platforms, as visual compasses (VCs) to provide an estimate of the rotational motion of the camera/robot from the omnidirectional video stream. Existing VC algorithms suffer from some practical limitations, since they require a precise knowledge either of the camera-calibration parameters, or the 3-D geometry of the observed scene. In this paper we present a novel multiple-view geometry constraint for paracatadioptric views of lines in 3-D, that we use to design a VC algorithm that does not require either the knowledge of the camera calibration parameters, or the 3-D scene geometry. In addition, our algorithm runs in real time since it relies on a closed-form estimate of the camera/robot rotation, and can address the image-feature correspondence problem. Extensive simulations and experiments with real robots have been performed to show the accuracy and robustness of the proposed method.     

Reliable and efficient landmark-based localization for mobile robots

This paper describes an efficient and robust localization system for indoor mobile robots and AGVs. The system utilizes a sensor that measures bearings to artificial landmarks, and an efficient triangulation method. We present a calibration method for the system components and overcome typical problems for sensors of the mentioned type, which are localization in motion and incorrect identification of landmarks. The resulting localization system was tested on a mobile robot. It consumes less than 4% of a Pentium4 3.2 GHz processing power while providing an accurate and reliable localization result every 0.5 s. The system was successfully incorporated within a real mobile robot system which performs many other computational tasks in parallel.     

Adaptive hierarchical positioning error compensation for long-term service of industrial robots based on incremental learning with fixed-length memory window and incremental model reconstruction

Industrial robots have been extensively used in industry, however, geometric errors mainly caused by connecting rod parameter error and non-geometric errors caused by deflection and friction, etc., limit its application in high-accuracy machining. Aiming at addressing these two types of errors, parametric methods for error compensation based on the kinematic model and non-parametric methods of directly establishing the mapping relationship between the actual and target poses of the robot end-effector are investigated and proposed. Currently both types of methods are mainly offline and will be no longer applicable when the pose of the end-effector in the workspace changes dramatically or the working performance of the robot degrades. Thus, to compensate the positioning error of an industrial robot during long-term operation, this research proposes an adaptive hierarchical compensation method based on fixed-length memory window incremental learning and incremental model reconstruction. Firstly, the correlation between positioning errors and robot poses is studied, a calibration sample library is created, and thus the actively evaluating mechanism of the pose mapping model is established to overcome the problem of the robot’ workspace having a differential distribution of error levels. Then, an incremental learning algorithm with fixed-length memory window and an incremental model reconstruction algorithm are designed to optimize the pose mapping model in terms of its parameters and architecture and overcome the problem that the performance degradation of the robot exacerbates the positioning error and affects the applicability of the pose mapping model, ensuring that the pose mapping model runs stably above the target accuracy level. Finally, the proposed method is applied to the long-term compensation case of a Stäubli industrial robot and a UR robot, and compared to state-of-art methods. Verification results show the proposed method reduces the position error of the Stäubli robot from 0.85mm to 0.13mm and orientation error from 0.68° to 0.07°, as well as reduces the position error of the UR robot from 2.11mm to 0.17mm, demonstrating that the proposed method works in real world scenarios and outperforms similar methods.     

Automatic work objects calibration via a global–local camera system

In a human–robot collaborative manufacturing application where a work object can be placed in an arbitrary position, there is a need to calibrate the actual position of the work object. This paper presents an approach for automatic work-object calibration in flexible robotic systems. The approach consists of two modules: a global positioning module based on fixed cameras mounted around robotic workspace, and a local positioning module based on the camera mounted on the robot arm. The aim of the global positioning is to detect the work object in the working area and roughly estimate its position, whereas the local positioning is to define an object frame according to the 3D position and orientation of the work object with higher accuracy. For object detection and localization, coded visual markers are utilized. For each object, several markers are used to increase the robustness and accuracy of the localization and calibration procedure. This approach can be used in robotic welding or assembly applications.     

嵌入式移动机器人红外路标定位模块研究

针对室内环境移动机器人的自定位问题,提出一种嵌入式移动机器人红外路标定位模块。采用基于单应矩阵的初始标定算法和陒机初始标定方法,补偿由于实际使用中的安装误差所引起的定位偏差。实验结果表明,该模块易于嵌入式系统实现,定位模块位置精度可达厘米级别,角度定位精度雓于6°。     

Three methodologies for the calibration of industrial manipulators: Experimental results on a SCARA robot

This article presents and compares three algorithms for the geometric parameter identification of industrial robots to increase its accuracy (static calibration). The estimation is based on the measure of the gripper pose errors when the robot follows suitable trajectories. The algorithms are general and can be applied to any robot providing that its kinematics is known. After a theoretical introduction to the general methodologies, these are applied to a selective compliance assembly robot arm (SCARA) robot analyzing its performance (precision, efficiency). Experimental results obtained with three methodologies are presented and discussed. The measure of the gripper pose error is based on a laser triangulation technique whose working principles are also recalled. © 2000 John Wiley & Sons, Inc.