scholarly journals Modeling and Identification of an Industrial Robot with a Selective Modal Approach

2020 ◽  
Vol 10 (13) ◽  
pp. 4619 ◽  
Author(s):  
Matteo Bottin ◽  
Silvio Cocuzza ◽  
Nicola Comand ◽  
Alberto Doria
Keyword(s):  
Dynamic Model ◽  
Material Removal ◽  
Industrial Robot ◽  
Joint Stiffness ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Robotic Assembly ◽  
Machined Surface ◽  
Modal Approach ◽  
Removal Processes

The stiffness properties of industrial robots are very important for many industrial applications, such as automatic robotic assembly and material removal processes (e.g., machining and deburring). On the one hand, in robotic assembly, joint compliance can be useful for compensating dimensional errors in the parts to be assembled; on the other hand, in material removal processes, a high Cartesian stiffness of the end-effector is required. Moreover, low frequency chatter vibrations can be induced when low-stiffness robots are used, with an impairment in the quality of the machined surface. In this paper, a compliant joint dynamic model of an industrial robot has been developed, in which joint stiffness has been experimentally identified using a modal approach. First, a novel method to select the test configurations has been developed, so that in each configuration the mode of vibration that chiefly involves only one joint is excited. Then, experimental tests are carried out in the selected configurations in order to identify joint stiffness. Finally, the developed dynamic model of the robot is used to predict the variation of the natural frequencies in the workspace.

scholarly journals Analysis of the Compliance Properties of an Industrial Robot with the Mozzi Axis Approach

Robotics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 80 ◽  
Author(s):  
Doria ◽  
Cocuzza ◽  
Comand ◽  
Bottin ◽  
Rossi
Keyword(s):  
Industrial Robot ◽  
Industrial Robots ◽  
Robotic Assembly ◽  
Robot Arm ◽  
Machined Surface ◽  
End Effector ◽  
Chatter Vibrations ◽  
Modes Of Vibration ◽  
Machining Robot ◽  
Robot Performance

In robotic processes, the compliance of the robot arm plays a very important role. In some conditions, for example, in robotic assembly, robot arm compliance can compensate for small position and orientation errors of the end-effector. In other processes, like machining, robot compliance may generate chatter vibrations with an impairment in the quality of the machined surface. In industrial robots, the compliance of the end-effector is chiefly due to joint compliances. In this paper, joint compliances of a serial six-joint industrial robot are identified with a novel modal method making use of specific modes of vibration dominated by the compliance of only one joint. Then, in order to represent the effect of the identified compliances on robot performance in an intuitive and geometric way, a novel kinematic method based on the concept of “Mozzi axis” of the end-effector is presented and discussed.

Study on Improving Accuracy in Robotic Milling of Aluminum Alloy

2018 ◽  
Author(s):  
Shaochun Sui ◽  
Kai Guo ◽  
Jie Sun ◽  
Yiran Zang
Keyword(s):  
Aluminum Alloy ◽  
Industrial Robot ◽  
Vibration Signal ◽  
Industrial Robots ◽  
Machining Process ◽  
Cnc Machine ◽  
Machined Surface ◽  
Improving Accuracy ◽  
High Level ◽  
Monolithic Components

Nowadays, the application of using industrial robots in manufacture is a diminutive due to its own low rigidity and low stiffness. This leads to high level of vibrations that limits the quality and the precision of the workpiece. So they are usually used for welding, grinding and paint shop. However, the potential of industrial robot applications in machining has be realized. The volume of monolithic components is large and there are many issues in machining process such as geometric tolerance and quality of machined surface. In such cases the traditional CNC machine is replaced by industrial robots, which will reduce the production cost, reduce labor and increase the efficiency. In this paper, the milling experiment of 7050-T7451 aeronautical aluminum alloy was carried out by using industrial robot KR210 R2700. In addition, the experiment was employed to study the influence of milling speed, feed-rate, cutting depth and cutting width on vibrations, surface roughness was also measured to evaluate the machining quality. Besides, the axis of angle was changed which led to the different industrial robot’s postures. The vibration signal of different postures was acquired, which was used to analysis the optimal workspace of industrial robot. The best process parameters were obtained, which will play a guiding significance on the actual production.

Analysis of non-geometric accuracy effects of articulated robots

2017 ◽  
Vol 44 (5) ◽  
pp. 639-647
Author(s):  
Gregor Lux ◽  
Marco Ulrich ◽  
Thomas Baker ◽  
Martin Hutterer ◽  
Gunther Reinhart
Keyword(s):  
Joint Stiffness ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Kinematic Structure ◽  
Geometric Accuracy ◽  
Robot Calibration ◽  
Content Type ◽  
Articulated Robots ◽  
Non Destructive ◽  
Geometric Effects

Purpose Articulated robots are widely used in industrial applications owing to their high repeatability accuracy. In terms of new applications such as robot-based inspection systems, the limitation is a lack of pose accuracy. Mostly, robot calibration approaches are used for the improvement of the pose accuracy. Such approaches however require a profound understanding of the determining effects. This paper aims to provide a non-destructive analysis method for the identification and characterisation of non-geometric accuracy effects in relation to the kinematic structure for the purpose of an accuracy enhancement. Design/methodology/approach The analysis is realised by a non-destructive method for rotational, uncoupled robot axes with the use of a 3D lasertracker. For each robot axis, the lasertracker position data for multiple reflectors are merged with the joint angles given by the robot controller. Based on this, the joint characteristics are determined. Furthermore, the influence of the kinematic structure is investigated. Findings This paper analyses the influence of the kinematic structure and non-geometric effects on the pose accuracy of standard articulated robots. The provided method is shown for two different industrial robots and presented effects incorporate tilting of the robot, torsional joint stiffness, hysteresis, influence of counter balance systems, as well as wear and damage. Practical implications Based on these results, an improved robot model for a better match between the mathematical description and the real robot system can be achieved by characterising non-geometric effects. In addition, wear and damages can be identified without a disassembly of the system. Originality/value The presented method for the analysis of non-geometric effects can be used in general for rotational, uncoupled robot axes. Furthermore, the investigated accuracy influencing effects can be taken into account to realise high-accuracy applications.

scholarly journals Joint Stiffness Identification and Deformation Compensation of Serial Robots Based on Dual Quaternion Algebra

2018 ◽  
Vol 9 (1) ◽  
pp. 65 ◽  
Author(s):  
Guozhi Li ◽  
Fuhai Zhang ◽  
Yili Fu ◽  
Shuguo Wang
Keyword(s):  
Quaternion Algebra ◽  
Industrial Robot ◽  
Joint Stiffness ◽  
Industrial Robots ◽  
Identification Algorithm ◽  
Dual Quaternion ◽  
Compensation Algorithm ◽  
Serial Robots ◽  
Stiffness Identification ◽  
Deformation Compensation

As the application of industrial robots is limited by low stiffness that causes low precision, a joint stiffness identification algorithm for serial robots is presented. In addition, a deformation compensation algorithm is proposed for the accuracy improvement. Both of these algorithms are formulated by dual quaternion algebra, which offers a compact, efficient, and singularity-free way in robot analysis. The joint stiffness identification algorithm is derived from stiffness modeling, which is the combination of the principle of virtual work and dual quaternion algebra. To validate the effectiveness of the proposed identification algorithm and deformation compensation algorithm, an experiment was conducted on a dual arm industrial robot SDA5F. The robot performed a drilling operation during the experiment, and the forces and torques that acted on the end-effector (EE) of both arms were measured in order to apply the deformation compensation algorithm. The results of the experiment show that the proposed identification algorithm is able to identify the joint stiffness parameters of serial industrial robots, and the deformation compensation algorithm can improve the accuracy of the position and orientation of the EE. Furthermore, the performance of the forces and torques that acted on the EE during the operation were improved as well.

Software Framework for Robot-Assisted Large Structure Assembly

2018 ◽  
Author(s):  
Shuyang Chen ◽  
Yuan-Chi Peng ◽  
John Wason ◽  
Jinda Cui ◽  
Glenn Saunders ◽  
...  
Keyword(s):  
Industrial Robot ◽  
Industrial Robots ◽  
Robotic Assembly ◽  
Software Framework ◽  
Multiple Sensors ◽  
Robot Positioning ◽  
Autonomous Assembly ◽  
Visualization And Simulation ◽  
Joint Limits ◽  
Structure Assembly

This paper presents the design and initial results of a project involving the robotic assembly of a large segmented structure. This project aims to develop an operator-guided semi-autonomous assembly process using industrial robots integrated with multiple sensors. The goal is to demonstrate the potential of robotic technology to reduce cycle time, enhance assembly quality, and improve worker ergonomics, as compared to the current manual or fixture-based approaches. The focus is primarily on the software framework which is composed of a collection of commercial and customized components for robot positioning, motion planning, low latency teleoperation, visualization and simulation. A foundation step of the implementation is safe teleoperation which allows the user to operate the robot without concern of collision or joint limits. The concept has been demonstrated in RobotStudio, the simulation environment for ABB robots, and a physical ABB robot. While some of the software is specific to the ABB industrial robot used in the project, the framework is readily adapted to other industrial robots that allow externally commanded motion.

scholarly journals A Methodology for Industrial Robot Calibration Based on Measurement Sub-Regions

2021 ◽  
Author(s):  
Juan Sebastian Toquica ◽  
José Maurı́cio Motta
Keyword(s):  
Industrial Robot ◽  
Low Cost ◽  
Kinematic Model ◽  
Measurement Data ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Robot Calibration ◽  
High Precision Measurement ◽  
Measurement Systems ◽  
Robot Accuracy

Abstract This paper proposes a methodology for calibration of industrial robots that uses a concept of measurement sub-regions, allowing low-cost solutions and easy implementation to meet the robot accuracy requirements in industrial applications. The solutions to increasing the accuracy of robots today have high-cost implementation, making calibration throughout the workplace in industry a difficult and unlikely task. Thus, reducing the time spent and the measured workspace volume of the robot end-effector are the main benefits of the implementation of the sub-region concept, ensuring sufficient flexibility in the measurement step of robot calibration procedures. The main contribution of this article is the proposal and discussion of a methodology to calibrate robots using several small measurement sub-regions and gathering the measurement data in a way equivalent to the measurements made in large volume regions, making feasible the use of high-precision measurement systems but limited to small volumes, such as vision-based measurement systems. The robot calibration procedures were simulated according to the literature, such that results from simulation are free from errors due to experimental setups as to isolate the benefits of the measurement proposal methodology. In addition, a method to validate the analytical off-line kinematic model of industrial robots is proposed using the nominal model of the robot supplier incorporated into its controller.

scholarly journals A dynamic parameter identification method of industrial robots considering joint elasticity

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141882521 ◽  
Author(s):  
Hepeng Ni ◽  
Chengrui Zhang ◽  
Tianliang Hu ◽  
Teng Wang ◽  
Qizhi Chen ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Dynamic Model ◽  
Joint Stiffness ◽  
Dynamic Parameter ◽  
Industrial Robots ◽  
Identification Accuracy ◽  
Processing Algorithm ◽  
Identification Method ◽  
Joint Elasticity ◽  
Dynamic Parameter Identification

Considering the joint elasticity, a novel dynamic parameter identification method is proposed for general industrial robots only with motor encoders. Firstly, the unknown parameters of the elastic joint dynamic model are analyzed and divided into two types. The first type is the motion-independent parameter only including the joint stiffness, which can be identified by the static force/torque-deformation experiments without the dynamic model. The second type is the motion-dependent parameter composed of the rest of the parameters, which needs the dynamic excitation experiments. Therefore, these two types of parameters can be identified separately. Meanwhile, it is found that the rotor inertia parameters can be obtained from the manufacturer, which reduces the identification difficulty of other parameters. After obtaining the rotor inertia and joint stiffness, an approximate processing algorithm is proposed considering the motor friction to establish the linear identification model of other parameters. Hence, the least squares can be employed to identify the parameters, and the independence of the inertia and joint viscous friction parameters are not affected. Meanwhile, the exciting trajectories can be optimized throughout the robot workspace, which reduces the effect of measurement noise on identification accuracy. With the proposed separated identification strategy and approximate processing algorithm, the dynamic parameters can be obtained precisely without double encoders on each joint. Finally, a series of simulations are conducted to evaluate the good performance of the proposed method.

Statistical Learning Algorithms to Compensate Slow Visual Feedback for Industrial Robots

2014 ◽  
Vol 137 (3) ◽  
Author(s):  
Cong Wang ◽  
Chung-Yen Lin ◽  
Masayoshi Tomizuka
Keyword(s):  
Real Time ◽  
Statistical Learning ◽  
Visual Feedback ◽  
Manufacturing Industry ◽  
Industrial Robot ◽  
Sampling Rate ◽  
Robot Vision ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Imaging Geometry

Vision guided robots have become an important element in the manufacturing industry. In most current industrial applications, vision guided robots are controlled by a look-then-move method. This method cannot support many new emerging demands which require real-time vision guidance. Challenge comes from the speed of visual feedback. Due to cost limit, industrial robot vision systems are subject to considerable latency and limited sampling rate. This paper proposes new algorithms to address this challenge by compensating the latency and slow sampling of visual feedback so that real-time vision guided robot control can be realized with satisfactory performance. Statistical learning methods are developed to model the pattern of target's motion adaptively. The learned model is used to recover visual measurement from latency and slow sampling. The imaging geometry of the camera and all-dimensional motion of the target are fully considered. Tests are conducted to provide evaluation from different aspects.

scholarly journals Sensor-Guided Assembly of Segmented Structures with Industrial Robots

2021 ◽  
Vol 11 (6) ◽  
pp. 2669
Author(s):  
Yuan-Chih Peng ◽  
Shuyang Chen ◽  
Devavrat Jivani ◽  
John Wason ◽  
William Lawler ◽  
...  
Keyword(s):  
Composite Structures ◽  
Industrial Robot ◽  
Robot Vision ◽  
Laminated Composite ◽  
Ground Truth ◽  
Industrial Robots ◽  
Robotic Assembly ◽  
Assembly Process ◽  
Finite State ◽  
Robot Wrist

This paper presents a robotic assembly methodology for the manufacturing of large segmented composite structures. The approach addresses three key steps in the assembly process: panel localization and pick-up, panel transport, and panel placement. Multiple stationary and robot-mounted cameras provide information for localization and alignment. A robot wrist-mounted force/torque sensor enables gentle but secure panel pick-up and placement. Human-assisted path planning ensures reliable collision-free motion of the robot with a large load in a tight space. A finite state machine governs the process flow and user interface. It allows process interruption and return to the previous known state in case of error condition or when secondary operations are needed. For performance verification, a high resolution motion capture system provides the ground truth reference. An experimental testbed integrating an industrial robot, vision and force sensors, and representative laminated composite panels demonstrates the feasibility of the proposed assembly process. Experimental results show sub-millimeter placement accuracy with shorter cycle times, lower contact force, and reduced panel oscillation than manual operations. This work demonstrates the versatility of sensor guided robotic assembly operation in a complex end-to-end tasks using the open source Robot Operating System (ROS) software framework.

scholarly journals Industrial Robots Fuel Cell Based Hybrid Power-Trains: A Comparison between Different Configurations

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1431
Author(s):  
Germán Andrés Ramos ◽  
Tomàs Montobbio de Pérez-Cabrero ◽  
Carles Domènech-Mestres ◽  
Ramon Costa-Castelló
Keyword(s):  
Fuel Cell ◽  
Electric Vehicles ◽  
Industrial Robot ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Hybrid Powertrain ◽  
Power Train ◽  
Hybrid Power ◽  
Bus Voltage ◽  
Hybrid Configuration

Electric vehicles are becoming more and more popular. One of the most promising possible solutions is one where a hybrid powertrain made up of a FC (Fuel Cell) and a battery is used. This type of vehicle offers great autonomy and high recharging speed, which makes them ideal for many industrial applications. In this work, three ways to build a hybrid power-train are presented and compared. To illustrate this, the case of an industrial robot designed to move loads within a fully automated factory is used. The analysis and comparison are carried out through different objective criteria that indicate the power-train performance in different battery charge levels. The hybrid configurations are tested using real power profiles of the industrial robot. Finally, simulation results show the performance of each hybrid configuration in terms of hydrogen consumption, battery and FC degradation, and dc bus voltage and current regulation.

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