Serial Industrial Robot Research Articles

At present, the absolute positioning accuracy and control accuracy of industrial serial robots need to be improved to meet the accuracy requirements of precision manufacturing and precise control. An accurate dynamic model is an important theoretical basis for solving this problem, and precise dynamic parameters are the prerequisite for precise control. The research of dynamics and parameter identification can greatly promote the application of robots in the field of precision manufacturing and automation. In this paper, we study the dynamical modeling and dynamic parameter identification of an industrial robot system with six rotational DOF (6R robot system) and propose a new method for identifying dynamic parameters. Our aim is to provide an accurate mathematical description of the dynamics of the 6R robot and to accurately identify its dynamic parameters. First, we establish an unconstrained dynamic model for the 6R robot system and rewrite it to obtain the dynamic parameter identification model. Second, we establish the constraint equations of the 6R robot system. Finally, we establish the dynamic model of the constrained 6R robot system. Through the ADAMS simulation experiment, we verify the correctness and accuracy of the dynamic model. The experiments prove that the result of parameter identification has extremely high accuracy and the dynamic model can accurately describe the 6R robot system mathematically. The dynamic modeling method proposed in this paper can be used as the theoretical basis for the study of 6R robot system dynamics and the study of dynamics-based control theory.

Industrial robots have been widely used in manufacturing for advantages of flexibility and high efficiency, while there exists a critical problem of low stiffness. Measuring the stiffnesses of joints accurately have a positive effect on optimizing the stiffness through compensation or posture adjustment. This study proposed a new method for stiffness identification of serial industrial robots using 3D digital image correlation (3D-DIC) techniques, which exhibits high accuracies. External forces are applied to the robot end and its 6-dimensional displacements are recorded with a 3D-DIC system. The values of joint stiffness are evaluated from the data of robot configurations, displacements and forces. The proposed method is implemented on the KUKA KR600-2830 robot experimentally and the average absolute value of relative error is 5.8%, which demonstrates that the proposed method provides much improved accuracy compared to the traditional method.

Dental implant surgery is an effective method for remediating the loss of teeth. Robot is expected to increase the accuracy of dental implant surgery. However, most of them are industrial serial robot, with low stiffness and non-unique inverse kinematic solution, which may reduce the success rate and safety of robotic surgery. Compared to serial robot, parallel robot is more stiffness and has unique inverse kinematic. However, its workspace is small, which may not meet surgical requirements. Therefore, a novel hybrid robot dedicated to dental implant is proposed. The hybrid robot is composed of three translation joints, two revolute joints, and Stewart parallel manipulator. Stewart is used for performing surgical operation, while the joints are used for enlarging the workspace of Stewart. In order to ensure the safety of robot motion, physical human-robot interaction based on a variable admittance controller is applied in the robotic system. In addition, considering the small workspace of Stewart, an optimal model is proposed to minimize the joint movement of Stewart in adjusting the orientation of drill bit. Phantom experiments were carried out based on the prototype robot. In the experiments, the optimal model could be solved after 20 iterations, finding an ideal joint configuration. The proposed variable admittance controller could enhance comfort level effectively. The accuracy of robot is evaluated by angle, entry and exit deviation, which are 0.74 ± 0.25°, 0.93 ± 0.28mm, and 0.96 ± 0.23mm, respectively. The phantom experiments validate the functionality of the proposed hybrid robot. The satisfactory performance makes it more widely used in the practical dental implant surgery in the future.

Based on the established serial 6-DOF robot calibration experiment platform, this paper aims to analyze and compare the effects of four error compensation methods, which are pseudotarget iteration-based error compensation method with three different forms and the Newton–Raphson-based error compensation method. Firstly, the pose error model of the serial robot is established based on the M-DH model in this paper. The calibration results show that the accuracy of the Staubli TX60 robot has been greatly improved. The average comprehensive position accuracy is increased by 88.7%, and the average comprehensive attitude accuracy is increased by 56.6%. Secondly, the principles of the four error compensation methods are discussed, and the effectiveness of the four error compensation methods are compared through experiments. The results show that the four error compensation methods can achieve error compensation well. The compensation accuracy is consistent with the identification accuracy of the kinematic model. The pseudotarget iteration with differential form has the best performance by the comprehensive consideration of accuracy and computational efficiency. Error compensation determines whether the accuracy of the identified model can be achieved. This paper presents a systematic experimental validation research on the effectiveness of four error compensation methods, which provides a reliable reference for the kinematic error compensation of industrial robots.

Abstract Most industrial serial robots use decentralized joint controllers assuming rigid body dynamics. To prevent exciting the flexible mode, gains are kept low, resulting in poor control bandwidth and disturbance rejection. In this paper, a two-stage flexible joint discrete controller is presented, in which the decentralized approach is extended with a stiffness to take into account the dominant coupling mode. In the first-stage, an input shaping feedforward shapes the rigid closed-loop dynamics into desired dynamics that does not produce link vibrations. Robotic dynamic computation based on a recursive Newton–Euler algorithm is conducted to update the feedforward link inertia parameter during robot motion. A second-stage is added to increase disturbance rejection. A generalized Smith predictor (GSP) is developed to compensate for delay and feedback sensor filtering. An effective methodology is presented to optimize the control loop gains. Numerical simulations and experiments on a six-joint robot manipulator confirm that the proposed controller improves control performances in terms of bandwidth, vibration attenuation, and disturbance rejection.

This paper proposes a new positioning accuracy reliability analysis method based on the differential kinematics and saddlepoint approximation to evaluate the influence of kinematic parameter uncertainties on the robotic motion. Firstly, considering the reliability analysis instability caused by complex nonlinear limit state function, the reliability model of positioning accuracy is established based on the differential kinematics and error propagation. Subsequently, the parameters of the position error distribution are deduced analytically to combine with the eigen-decomposition to complete the modeling of the cumulant generating function, thereby the kinematic reliability is yielded according to the saddlepoint approximation method. Finally, the comparative analysis of a six degrees of freedom serial industrial robot is conducted and the results of which demonstrate that the proposed method provides a better performance than the existing methods in terms of accuracy and efficiency for kinematic reliability analysis.

SUMMARYIn typical calibration methods (kinematic or non-kinematic) for serial industrial robot, though measurement instruments with high resolutions are adopted, measurement configurations are optimized, and redundant parameters are eliminated from identification model, calibration accuracy is still limited under measurement noise. This might be because huge gaps still exist among the singular values of typical identification Jacobians, thereby causing the identification models ill conditioned. This paper addresses such problem by using new identification models established in two steps. First, the typical models are divided into the submodels with truncated singular values. In this way, the unknown parameters corresponding to the abnormal singular values are removed, thereby reducing the condition numbers of the new submodels. However, these models might still be ill conditioned. Therefore, the second step is to further centralize the singular values of each submodel by using a matrix balance method. Afterward, all submodels are well conditioned and obtain much higher observability indices compared with those of typical models. Simulation results indicate that significant improvements in the stability of identification results and the identifiability of unknown parameters are acquired by using the new identification submodels. Experimental results indicate that the proposed calibration method increases the identification accuracy without incurring additional hardware setup costs to the typical calibration method.

Incremental forming with contact between tool-sheet metal workpiece in a single point is an unconventional process which allow the user to manufacture parts by combining the vertical movement of the tool along Z-axis and the horizontal movements of sheet metal workpiece, which are performed in XY plane. As technological equipment able to control coordinated movements on three axes, CNC machining centers and industrial serial robots with six degrees of freedom are the most suitable. The paper introduces a study regarding the use of robots as technological equipment for the process, by means of simulation. Supplementary degrees of freedom and singularities avoidance are also considered.

Virtual reality tracking devices are rapidly becoming the go-to system for cost-effective motion tracking solutions across different communities such as robotics, biomechanics, sports, rehabilitation, motion simulators, etc. This article focuses on the spatial tracking performance of HTC Vive's lighthouse tracking system (VLTS) devices (tracker, controller, and head mount display). A comprehensive literature survey on the performance analysis of VLTS on the various aspects is presented along with its shortcomings in terms of spatial tracking evaluation. The two key limitations have been identified: in static cases, there is a lack of standard procedures and criteria, and in dynamic cases, the entire study of spatial tracking. We address the first by assessing VLTS using the optical tracking system standard specified by ASTM International, and the latter by revising the standards to determine the upper-velocity limit for reliable tracking. The findings are substantiated with the trajectories of human wrist motion. Each evaluation's results are systematically analyzed with statistical hypothesis tests and criteria fulfillment. Comau NS16, an industrial serial robot, was used as the ground truth motion generator due to its repeatability and 6 degrees of workspace freedom. One of the major reasons for not having more generalized spatial tracking studies is that the tracking performance heavily depends on the configurations of the setup, work volume, environment, etc. Thus, the guidelines for configuring VLTS and the approach adapted from ASTM standards for evaluating VLTS for custom applications using our reported findings for both static and dynamic cases are included in the appendix.

Most driving torques in serial industrial robots are used to overcome the weight of the robot. Although actuators account for a large proportion of the total mass of a robot, they have yet to become a positive factor that enables the robot to achieve gravity balance. This study presents a host–parasite structure to reconstruct the distribution of actuators and achieve gravity balance in robots. First, based on the characteristics of tree–rattan mechanisms, a method for calculating the degrees of freedom and a symbolic representation method for the distribution of branched chains are formulated for host–parasite mechanisms. Second, a configuration analysis and optimization method for host–parasite structure-based robots and a robot prototype are presented. Finally, four host–parasite mechanisms/robots (A, B, C, and D) are compared. The results are as follows. If more parasitic branched chains are added to the yz plane, the loads along axes 2 and 3 become more balanced, which significantly increases the stiffnesses of the mechanism in the y- and z-directions ( Ky and Kz, respectively). If the additional branched chains are closer to the site of maximum deformation, the stiffness of the mechanism in the z-direction ( Kz) increases more significantly. Of the four mechanisms, mechanism D has the best overall performance. The joint torques of mechanism D along axes 2 and 3 are lower than those of mechanism A by 99.78% and 99.18%, respectively. In addition, Kx, Ky, and Kz of mechanism D are 100.56%, 336.19%, and 385.02% of those of mechanism A, respectively. Moreover, the first-order natural frequency of mechanism D is 135.94% of that of mechanism A. Host–parasitic structure is conducive to improving the performance of industrial robots.

ABSTRACT Robot-CT is drawing great attention for its potential to support highly flexible scan trajectories and various scan modes with a single system. However, the quality of CT reconstruction largely depends on accurate knowledge of the scan geometry, i.e. position and orientation of the source and the detector. This imposes major challenges on current serial industrial robots. In order to realistically assess the impact of various robot characteristics on the Robot-CT reconstruction quality and to facilitate the development of a dedicated calibration method, this paper elaborates on a set of simulations based on the performance evaluation of an ABB industrial robot. Simulation results reveal that: (a) synchronous error motions of the twin robots can partially compensate for the robot errors; (b) offline calibration is a possible way to implement high accuracy Robot-CT due to the excellent repeatability of current industrial robots; (c) both robot positioning and orientation errors need to be compensated for to get a high quality reconstruction; (d) compensating for only the relative error cannot improve the final reconstruction quality: absolute positioning and orientation errors need to be measured and compensated for. External sensors or radiograph based absolute geometry calibration are needed to improve the reconstruction quality.

In the application process of industrial robots, it is necessary to ensure that the home position is correct when the robot changes the end tool, so that the coordinate values of tool can be calculated more accurately and the accuracy of the robot’s trajectory can be satisfied. A comprehensive calibration method of tool coordinates and home position of serial industrial robots based on fixed-point constraints is presented in this paper. Based on Denavit-Hartenberg (D-H) kinematics theory, the error models of tool coordinates and home position errors of 6-DOF serial industrial robots are established. By constraining the tool center point (TCP) of the robot with fixed points, the joint data of calibration points with different postures at the same position are collected, and the error value of the controlled object is identified by the least square algorithm. The calibration experiment results are basically consistent with the factory calibration parameters, which proves the feasibility of the calibration algorithm.

Serial robots are the most used today and among them, the most common is the basic 3R module, the module that is developed in the vast majority of anthropomorphic serial industrial robots, which today occupies at least 80-90% of the total industrial robots existing worldwide. One studied the kinematics and the forces in this module in other works, with an emphasis on the inverse kinematics, so that in this paper the authors will deal with the dynamic functioning of this 3R structure, a basic structure as it could be observed, because the dynamics which represent in fact the actual operation of the entire robotic structure is, therefore, the most important in operation, both for the optimal analysis or design of the robotic structure, as well as for its implementation or maintenance throughout its life. The paper presents the real dynamic functioning of the 3R structure, the related calculation relationships and the diagrams with the simulation of the real dynamic functioning of the 3R platform.

Inaccuracy of the kinematic model used in robot controllers and deflection of robot joints are two main sources of positioning errors in current industrial robots. We propose an elasto-geometrical calibration method to address these problems. The elasto-geometrical calibration identifies the accurate kinematic model and joint elasticities of any industrial serial robot by measuring the robot tool position at multiple design points. Each design point indicates a unique combination of a robot configuration (set of joint values) and an external load on the robot tool. Proper selection of the design points could significantly improve the calibration accuracy and reduce the experiment time. We propose an optimal design of experiment to find the D-, A-, and E-optimal designs from a large pool of candidate design points. Unlike the existing approaches, we use a semidefinite convex programming that can find a suboptimal design of experiments. The efficiency of the proposed elasto-geometrical calibration is evaluated on an ABB IRB 1600 robot. For this experiment, a cable-driven parallel robot is employed to apply multidirectional external loads on the tool of the ABB robot. Experimental results show that the proposed calibration method significantly improves the robot's accuracy in comparison with a regular kinematic calibration method. In addition, the D-optimal design results in less positioning error than A- and E-optimal designs.

Abstract Robots are important in high-mix low-volume manufacturing because of their versatility and repeatability in performing manufacturing tasks. However, robots have not been widely used due to cumbersome programming effort and lack of operator skill. One significant factor prohibiting the widespread application of robots by small and medium enterprises (SMEs) is the high cost and necessary skill of programming and re-programming robots to perform diverse tasks. This paper discusses an Augmented Reality (AR) assisted robot programming system (ARRPS) that provides faster and more intuitive robot programming than conventional techniques. ARRPS is designed to allow users with little robot programming knowledge to program tasks for a serial robot. The system transforms the work cell of a serial industrial robot into an AR environment. With an AR user interface and a handheld pointer for interaction, users are free to move around the work cell to define 3D points and paths for the real robot to follow. Sensor data and algorithms are used for robot motion planning, collision detection and plan validation. The proposed approach enables fast and intuitive robotic path and task programming, and allows users to focus only on the definition of tasks. The implementation of this AR-assisted robot system is presented, and specific methods to enhance the performance of the users in carrying out robot programming using this system are highlighted.

Industrial serial robots can be classified according to several criteria, the most important being: the number of mobility degrees or independent movements, the number of independent kinematic axes, the shape of the workspace, the value of the useful load, the precision of touching a predetermined point, etc. Among these criteria, the number of degrees of mobility directly determines the structure of the kinematic chain corresponding to the robot and implicitly its construction, functionality and utility. In this paper, we define the three classes of industrial serial robots according to the degree of mobility: the class of industrial serial robots of minimum configuration, the class of redundant industrial serial robots and the class of hyper-redundant industrial serial robots. For each class of industrial serial robots the structural synthesis method is presented and representative examples of structures are given.

For the first, the industrial serial robots can be classified according the number of mobility degrees or independent movements, the number of independent kinematic axes, the shape of the workspace, the value of the useful load, the precision of touching a predetermined point, etc. The number of degrees of mobility directly determines the structure of the kinematic chain corresponding to the robot and implicitly its construction, functionality and utility. In this paper, we define the class of redundant industrial serial robots. For the redundant industrial serial robots the structural synthesis method is presented and for each type of representative examples of structures are given.

The quality of industrial robots essentially depends on the properties of their kinematic couples. This research has involved conducting an experimental study of the friction torque in a joint of the KUKA KR10 industrial robot and building its model. It has been established that the largest impact on friction in the joint is caused by its axial load and velocity, as well as the temperature of the mechanism, which is generally not homogeneous. It is not possible to measure temperature fields in the joints of a serial industrial robot directly. This study has set forth a method to estimate friction torque taking into account the temperature factor indirectly. For this, we have used the motor temperature available for measuring in combination with special periodical motions, performed by the robot, during which we estimated the actual friction torque in the joint and calculated a temperature correction based on our findings.

Incremental forming can be usually unfolded either on CNC milling machine–tools or serial industrial robots. The approach proposed in this paper tackles the problem of designing a modular fastening system, which can be adapted for both above mentioned technological equipment. The fastening system of the sheet–metal workpiece is composed of a fixing plate and a retaining plate. The fixing and retaining plates will be made up of different individual elements, which can be easily repositioned to obtain different sizes of the part. Moreover, the fastening system has to be able to be positioned either horizontally (to be fitted on CNC milling machines) or vertically (to be fitted on industrial robots. The paper also presents the design of a tool–holder working unit which will be fitted on KUKA KR 210 industrial robot. The working unit will be mounted as end–effector of the robot and will bear the punch, driving it on the processing toolpaths.

This paper presents a method for optimizing the trajectories of robotic arms having manipulators with six degrees of freedom (DOFs) and spherical wrists. The trajectories are optimized by maximizing the manipulator performance (manipulability). For this purpose, kinematics models of the robot arms are defined, such that they can be integrated into an algorithm based on the Kalman filter. This algorithm is implemented through the simulation of trajectories in a serial industrial robot, which is a robotic arm with six DOFs and a fitted welding tool with a material contribution. During the trajectory optimization for such a manipulator robot, the orientation of the welding gun (e.g., the position of the final effector) must be preserved to guarantee correct welding. Applications of this method to two trajectories in the automotive industry are presented, and remarkable improvements in the performance of the manipulator itself are observed. The results obtained demonstrate that the proposed algorithm is an appropriate method for optimizing trajectories because of its various advantages, such as ease of implementation and states of calculation based only on the previous states. Therefore, this method allows the trajectories to be optimized in the work environment of the robot once the kinematic parameters of a robotic manipulator arm are known.