Uncertainty evaluation of measurement of orientation repeatability for industrial robots

2020 ◽  
Vol 47 (2) ◽  
pp. 207-217
Author(s):  
Yang Chuangui ◽  
Mi Liang ◽  
Liu Xingbao ◽  
Xia Yangqiu ◽  
Qiang Teng ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Linear Problem ◽  
Industrial Robot ◽  
Measurement Model ◽  
Industrial Robots ◽  
Uncertainty Evaluation ◽  
Laser Tracker ◽  
Uncertainty Of Measurement ◽  
Content Type ◽  
Non Linear

Purpose This paper aims to propose a reasonable method to evaluate uncertainty of measurement of industrial robots’ orientation repeatability and solve the non-linear problem existing in its evaluation procedure. Design/methodology/approach Firstly, a measurement model of orientation repeatability, based on laser tracker, is established. Secondly, some factors, influencing the measurement result of orientation repeatability, are identified, and their probability distribution functions are modelled. Thirdly, based on Monte Carlo method, an uncertainty evaluation model and algorithm of measurement of industrial robot’s orientation repeatability are built. Finally, an industrial robot is taken as the research object to validate the rationality of proposed method. Findings Results show that the measurement model of orientation repeatability of industrial robot is non-linear, and the proposed method can reasonably and objectively estimate uncertainty of measurement of industrial robots’ orientation repeatability. Originality/value This paper, based on Monte Carlo method and experimental work, proposes an uncertainty evaluation method of measurement of industrial robots’ orientation repeatability which can solve the non-linear problem and provide a reasonable and objective evaluation. And the stochastic ellipsoid approach is firstly taken to model the repeatability of laser tracker. Additionally, this research is beneficial to decide whether the orientation repeatability of the industrial robot meets its requirements.

Uncertainty analysis and evaluation of measurement of the positioning repeatability for industrial robots

2018 ◽  
Vol 45 (4) ◽  
pp. 492-504 ◽  
Author(s):  
Yang Chuangui ◽  
Liu Xingbao ◽  
Yue Xiaobin ◽  
Mi Liang ◽  
Wang Junwen ◽  
...  
Keyword(s):  
Probability Distribution Function ◽  
Design Methodology ◽  
Industrial Robot ◽  
Measurement Model ◽  
Measurement Procedure ◽  
Industrial Robots ◽  
Key Factors ◽  
Content Type ◽  
Normal Distributions ◽  
Analysis And Evaluation

PurposeThis paper aims to solve the nonlinear problem in the uncertainty evaluation of the measurement of the positioning repeatability (RP) of industrial robots and provide guidance to restrict the uncertainty of measurement of RP (uRP).Design/methodology/approachFirstly, some uncertain sources existing in the measurement procedure of RP are identified. Secondly, the probability distribution function (PDF) of every source is established on the basis of its measurements. Some spatial combined normal distributions are adopted. Then, a method, based on Monte Carlo method (MCM) and established measurement model, is developed for the estimation ofuRP. Thirdly, some tests are developed for the identification and validation of the selected PDFs of uncertain sources. Afterwards, the proposed method is applied for the evaluation and validation of theuRP. Finally, influence analyses of some key factors are proposed for the quantification of their relative contributions touRP.FindingsResults show that the proposed method can reasonably and objectively estimate theuRPof the selected industrial robot, and changes of the industrial robots’ position and the laser trackers measurement are correlated. Additionally, theuRPof the selected industrial robot can be restricted by using the results of its key factors onuRP.Originality/valueThis paper proposes the spatial combined normal distribution to model the uncertainty of the repeatability of the laser tracker and industrial robot. Meanwhile, the proposed method and influence analyses can be used in estimating and restricting theuRPand thus useful in determining whether the RP of a tested industrial robot meets its requirements.

A comparative evaluation of three industrial robots using three reference measuring techniques

2015 ◽  
Vol 42 (6) ◽  
pp. 572-585 ◽  
Author(s):  
Mohamed Slamani ◽  
Ahmed Joubair ◽  
Ilian A. Bonev
Keyword(s):  
Manufacturing Systems ◽  
Tool Path ◽  
Laser Interferometer ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Laser Tracker ◽  
Specific Test ◽  
Reference Measuring ◽  
Content Type ◽  
Robot Selection

Purpose – The purpose of this paper is to present a technique for assessing and comparing the static and dynamic performance of three different models of small six-axis industrial robots using a Renishaw XL80 laser interferometer system, a FARO ION laser tracker and a Renishaw QC20-W telescoping ballbar. Design/methodology/approach – Specific test methods are proposed in this work, and each robot has been measured in a similar area of its working envelope. The laser interferometer measurement instrument is used to assess the static positioning performance along three linear and orthogonal paths. The laser tracker is used to assess the contouring performance at different tool center point (TCP) speeds along a triangular tool path, whereas the telescoping ballbar is used to assess the dynamic positioning performance for circular paths at different TCP speeds and trajectory radii. Findings – It is found that the tested robots behave differently, and that the static accuracy of these non-calibrated robots varies between 0.5 and 2.3 mm. On the other hand, results show that these three robots can provide acceptable corner tracking at low TCP speeds. However, a significant overshoot at the corner is observed at high TCP speed for all the robots tested. It was also found that the smallest increment of Cartesian displacement (Cartesian resolution) that can be taken by the tested robots is approximately 50 μm. Practical implications – The technique used in this paper allows extremely accurate diagnosis of the robot performance, which makes it possible for the robot user to determine whether the robot is in good or bad condition. It can also help the decision-maker to select the most suitable industrial robot to achieve the desired task with minimum cost and specific application ability. Originality/value – This paper proposed a new method based on the performance verification approach for solving the robot selection problem for flexible manufacturing systems. Furthermore, despite their importance, bidirectional repeatability and Cartesian resolution are never specified by the manufacturers of industrial robots nor are they described in the ISO 9283:1998 guide, and they are rarely the object of performance assessments. In this work, specific tests are performed to check and quantify the bidirectional repeatability and the Cartesian resolution of each robot.

A four-point measurement model for evaluating the pose of industrial robot and its influence factor analysis

2017 ◽  
Vol 44 (3) ◽  
pp. 343-352 ◽  
Author(s):  
Chuangui Yang ◽  
Junwen Wang ◽  
Liang Mi ◽  
Xingbao Liu ◽  
Yangqiu Xia ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Measurement Uncertainty ◽  
Measurement Accuracy ◽  
Influence Factor ◽  
Industrial Robot ◽  
Measurement Model ◽  
Industrial Robots ◽  
Content Type ◽  
Point Measurement ◽  
Proposed Model

Purpose This paper aims to propose a four-point measurement model for directly measuring the pose (i.e. position and orientation) of industrial robot and reducing its calculating error and measurement uncertainty. Design/methodology/approach A four-point measurement model is proposed for directly measuring poses of industrial robots. First, this model consists of a position measurement model and an orientation model gotten by the position of spherically mounted reflector (SMR). Second, an influence factor analysis, simulated by Monte Carlo simulation, is performed to investigate the influence of certain factors on the accuracy and uncertainty. Third, comparisons with the common method are carried out to verify the advantage of this model. Finally, a test is carried out for evaluating the repeatability of five poses of an industrial robot. Findings In this paper, results show that the proposed model is better than the three-SMRs model in measurement accuracy, measurement uncertainty and computational efficiency. Moreover, both measurement accuracy and measurement uncertainty can be improved by using the proposed influence laws of its key parameters on the proposed model. Originality/value The proposed model can measure poses of industrial robots directly, accurately and effectively. Additionally, influence laws of key factors on the accuracy and uncertainty of the proposed model are given to provide some guidelines for improving the performance of the proposed model.

Optimization design of drive system for industrial robots based on dynamic performance

2017 ◽  
Vol 44 (6) ◽  
pp. 765-775 ◽  
Author(s):  
LianZheng Ge ◽  
Jian Chen ◽  
Ruifeng Li ◽  
Peidong Liang
Keyword(s):  
Optimization Model ◽  
Optimization Problem ◽  
Industrial Robot ◽  
Dynamic Performance ◽  
System Optimization ◽  
Drive System ◽  
Industrial Robots ◽  
Mixed Integer ◽  
Light Weight ◽  
Content Type

Purpose The global performance of industrial robots partly depends on the properties of drive system consisting of motor inertia, gearbox inertia, etc. This paper aims to deal with the problem of optimization of global dynamic performance for robotic drive system selected from available components. Design/methodology/approach Considering the performance specifications of drive system, an optimization model whose objective function is composed of working efficiency and natural frequency of robots is proposed. Meanwhile, constraints including the rated and peak torque of motor, lifetime of gearbox and light-weight were taken into account. Furthermore, the mapping relationship between discrete optimal design variables and component properties of drive system were presented. The optimization problem with mixed integer variables was solved by a mixed integer-laplace crossover power mutation algorithm. Findings The optimization results show that our optimization model and methods are applicable, and the performances are also greatly promoted without sacrificing any constraints of drive system. Besides, the model fits the overall performance well with respect to light-weight ratio, safety, cost reduction and others. Practical implications The proposed drive system optimization method has been used for a 4-DOF palletizing robot, which has been largely manufactured in a factory. Originality/value This paper focuses on how the simulation-based optimization can be used for the purpose of generating trade-offs between cost, performance and lifetime when designing robotic drive system. An applicable optimization model and method are proposed to handle the dynamic performance optimization problem of a drive system for industrial robot.

scholarly journals A new joint friction model for parameter identification and sensor-less hand guiding in industrial robots

2020 ◽  
Vol 47 (6) ◽  
pp. 847-857
Author(s):  
Guanghui Liu ◽  
Qiang Li ◽  
Lijin Fang ◽  
Bing Han ◽  
Hualiang Zhang
Keyword(s):  
Industrial Robot ◽  
Angular Displacement ◽  
Weighted Least Squares ◽  
Friction Model ◽  
Industrial Robots ◽  
Model Parameters ◽  
Dynamic Parameters ◽  
Content Type ◽  
Joint Friction ◽  
Six Dof

Purpose The purpose of this paper is to propose a new joint friction model, which can accurately model the real friction, especially in cases with sudden changes in the motion direction. The identification and sensor-less control algorithm are investigated to verify the validity of this model. Design/methodology/approach The proposed friction model is nonlinear and it considers the angular displacement and angular velocity of the joint as a secondary compensation for identification. In the present study, the authors design a pipeline – including a manually designed excitation trajectory, a weighted least squares algorithm for identifying the dynamic parameters and a hand guiding controller for the arm’s direct teaching. Findings Compared with the conventional joint friction model, the proposed method can effectively predict friction factors during the dynamic motion of the arm. Then friction parameters are quantitatively obtained and compared with the proposed friction model and the conventional friction model indirectly. It is found that the average root mean square error of predicted six joints in the proposed method decreases by more than 54%. The arm’s force control with the full torque using the estimated dynamic parameters is qualitatively studied. It is concluded that a light-weight industrial robot can be dragged smoothly by the hand guiding. Practical implications In the present study, a systematic pipeline is proposed for identifying and controlling an industrial arm. The whole procedure has been verified in a commercial six DOF industrial arm. Based on the conducted experiment, it is found that the proposed approach is more accurate in comparison with conventional methods. A hand-guiding demo also illustrates that the proposed approach can provide the industrial arm with the full torque compensation. This essential functionality is widely required in many industrial arms such as kinaesthetic teaching. Originality/value First, a new friction model is proposed. Based on this model, identifying the dynamic parameter is carried out to obtain a set of model parameters of an industrial arm. Finally, a smooth hand guiding control is demonstrated based on the proposed dynamic model.

Developing complex-project capability through dynamic organizational learning

2015 ◽  
Vol 8 (4) ◽  
pp. 732-754 ◽  
Author(s):  
Terence Ahern ◽  
P.J. Byrne ◽  
Brian Leavy
Keyword(s):  
Organizational Learning ◽  
Knowledge Creation ◽  
Linear Problem ◽  
Continuous Learning ◽  
Content Type ◽  
Complex Projects ◽  
Non Linear ◽  
Complex Project ◽  
Knowledge Uncertainty ◽  
Practical Implications

Purpose – The purpose of this paper is to extend the learning boundaries of traditional project capability, which follows the linear planning paradigm, in order to include non-linear complex projects that cannot be completely specified and planned in advance, and so require continuous learning over their life cycles. Design/methodology/approach – Based on an earlier empirical investigation, where complex-project capability (CPC) is developed through dynamic organizational learning based on non-linear problem solving, the paper examines some of the conceptual and practical implications of this process insight. The focus here is on incomplete pre-given knowledge and emergent knowledge creation during CPC development. Findings – Using the three interrelated dimensions of project type, knowledge creation method, and organizational learning approach, the paper reinterprets Karl Popper’s linear problem solving model for learning in traditional projects by introducing the concept of knowledge entropy (disorder) for learning in non-linear complex projects. The latter follows a path from “order to disorder to order” rather than from “order to order” under traditional assumptions. Research limitations/implications – By identifying a common learning process at individual, group, and organizational levels, developing CPC can be viewed as a “learning organization”. This multi-level approach facilitates research into distributed organizing for emergent knowledge creation during CPC development. Practical implications – In contrast to traditional planned projects with up-front prior knowledge, complex projects are characterized by incomplete knowledge. The challenge of dealing with knowledge uncertainty in complex projects through continuous learning has practical implications for project learning, planning, knowledge management, and leadership. Originality/value – The concept of knowledge entropy (disorder) extends the learning boundaries of traditional projects, where little learning is anticipated, by including complex projects with knowledge uncertainty requiring continuous learning.

Practical application of a safe human-robot interaction software

2020 ◽  
Vol 47 (3) ◽  
pp. 359-368 ◽  
Author(s):  
Mustafa Can Bingol ◽  
Omur Aydogmus
Keyword(s):  
Robot Manipulator ◽  
Industrial Robot ◽  
Wavelet Packet ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Robot Interaction ◽  
Content Type ◽  
Depth Sensors ◽  
Working Space ◽  
Vision Module

Purpose Because of the increased use of robots in the industry, it has become inevitable for humans and robots to be able to work together. Therefore, human security has become the primary noncompromising factor of joint human and robot operations. For this reason, the purpose of this study was to develop a safe human-robot interaction software based on vision and touch. Design/methodology/approach The software consists of three modules. Firstly, the vision module has two tasks: to determine whether there is a human presence and to measure the distance between the robot and the human within the robot’s working space using convolutional neural networks (CNNs) and depth sensors. Secondly, the touch detection module perceives whether or not a human physically touches the robot within the same work environment using robot axis torques, wavelet packet decomposition algorithm and CNN. Lastly, the robot’s operating speed is adjusted according to hazard levels came from vision and touch module using the robot’s control module. Findings The developed software was tested with an industrial robot manipulator and successful results were obtained with minimal error. Practical implications The success of the developed algorithm was demonstrated in the current study and the algorithm can be used in other industrial robots for safety. Originality/value In this study, a new and practical safety algorithm is proposed and the health of people working with industrial robots is guaranteed.

The integration of contactless static pose recognition and dynamic hand motion tracking control system for industrial human and robot collaboration

2015 ◽  
Vol 42 (5) ◽  
pp. 416-428 ◽  
Author(s):  
Gilbert Tang ◽  
Seemal Asif ◽  
Phil Webb
Keyword(s):  
Control System ◽  
Motion Tracking ◽  
Industrial Robot ◽  
Integrated System ◽  
Industrial Robots ◽  
Content Type ◽  
Hand Motion ◽  
Pose Recognition ◽  
Gesture Control ◽  
Potential Applications

Purpose – The purpose of this paper is to describe the integration of a gesture control system for industrial collaborative robot. Human and robot collaborative systems can be a viable manufacturing solution, but efficient control and communication are required for operations to be carried out effectively and safely. Design/methodology/approach – The integrated system consists of facial recognition, static pose recognition and dynamic hand motion tracking. Each sub-system has been tested in isolation before integration and demonstration of a sample task. Findings – It is demonstrated that the combination of multiple gesture control methods can increase its potential applications for industrial robots. Originality/value – The novelty of the system is the combination of a dual gesture controls method which allows operators to command an industrial robot by posing hand gestures as well as control the robot motion by moving one of their hands in front of the sensor. A facial verification system is integrated to improve the robustness, reliability and security of the control system which also allows assignment of permission levels to different users.

Acquisition of welding skills in industrial robots

2015 ◽  
Vol 42 (2) ◽  
pp. 156-166 ◽  
Author(s):  
J.F. Aviles-Viñas ◽  
I. Lopez-Juarez ◽  
R. Rios-Cabrera
Keyword(s):  
Real Time ◽  
Learning Process ◽  
Vision System ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Content Type ◽  
Welding Machine ◽  
Vision Algorithm

Purpose – The purpose of this paper was to propose a method based on an Artificial Neural Network and a real-time vision algorithm, to learn welding skills in industrial robotics. Design/methodology/approach – By using an optic camera to measure the bead geometry (width and height), the authors propose a real-time computer vision algorithm to extract training patterns and to enable an industrial robot to acquire and learn autonomously the welding skill. To test the approach, an industrial KUKA robot and a welding gas metal arc welding machine were used in a manufacturing cell. Findings – Several data analyses are described, showing empirically that industrial robots can acquire the skill even if the specific welding parameters are unknown. Research limitations/implications – The approach considers only stringer beads. Weave bead and bead penetration are not considered. Practical implications – With the proposed approach, it is possible to learn specific welding parameters despite of the material, type of robot or welding machine. This is due to the fact that the feedback system produces automatic measurements that are labelled prior to the learning process. Originality/value – The main contribution is that the complex learning process is reduced into an input-process-output system, where the process part is learnt automatically without human supervision, by registering the patterns with an automatically calibrated vision system.

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