High-precision six-degree-of-freedom pose measurement and grasping system for large-size object based on binocular vision

Sensor Review ◽  
2020 ◽  
Vol 40 (1) ◽  
pp. 71-80 ◽  
Author(s):  
Guoyang Wan ◽  
Fudong Li ◽  
Wenjun Zhu ◽  
Guofeng Wang
Keyword(s):  
Binocular Vision ◽  
Industrial Robot ◽  
Robot Vision ◽  
Positioning Accuracy ◽  
Content Type ◽  
High Position ◽  
Large Size ◽  
Positioning Strategy ◽  
Circular Holes ◽  
Six Degree Of Freedom

Purpose The positioning and grasping of large-size objects have always had problems of low positioning accuracy, slow grasping speed and high application cost compared with ordinary small parts tasks. This paper aims to propose and implement a binocular vision-guided grasping system for large-size object with industrial robot. Design/methodology/approach To guide the industrial robot to grasp the object with high position and pose accuracy, this study measures the pose of the object by extracting and reconstructing three non-collinear feature points on it. To improve the precision and the robustness of the pose measuring, a coarse-to-fine positioning strategy is proposed. First, a coarse but stable feature is chosen to locate the object in the image and provide initial regions for the fine features. Second, three circular holes are chosen to be the fine features whose centers are extracted with a robust ellipse fitting strategy and thus determine the precise pose and position of the object. Findings Experimental results show that the proposed system has achieved high robustness and high positioning accuracy of −1 mm and pose accuracy of −0.5 degree. Originality/value It is a high accuracy method that can be used for industrial robot vision-guided and grasp location.

A simple and rapid calibration methodology for industrial robot based on geometric constraint and two-step error

2018 ◽  
Vol 45 (6) ◽  
pp. 715-721 ◽  
Author(s):  
Jiabo Zhang ◽  
Xibin Wang ◽  
Ke Wen ◽  
Yinghao Zhou ◽  
Yi Yue ◽  
...  
Keyword(s):  
Coordinate System ◽  
Large Scale ◽  
Industrial Robot ◽  
Geometric Constraint ◽  
Machining Process ◽  
Kinematic Parameters ◽  
Robot Calibration ◽  
Positioning Accuracy ◽  
Content Type ◽  
Rapid Calibration

Purpose The purpose of this study is the presentation and research of a simple and rapid calibration methodology for industrial robot. Extensive research efforts were devoted to meet the requirements of online compensation, closed-loop feedback control and high-precision machining during the flexible machining process of robot for large-scale cabin. Design/methodology/approach A simple and rapid method to design and construct the transformation relation between the base coordinate system of robot and the measurement coordinate system was proposed based on geometric constraint. By establishing the Denavit–Hartenberg model for robot calibration, a method of two-step error for kinematic parameters calibration was put forward, which aided in achievement of step-by-step calibration of angle and distance errors. Furthermore, KUKA robot was considered as the research object, and related experiments were performed based on laser tracker. Findings The experimental results demonstrated that the accuracy of the coordinate transformation could reach 0.128 mm, which meets the transformation requirements. Compared to other methods used in this study, the calibration method of two-step error could significantly improve the positioning accuracy of robot up to 0.271 mm. Originality/value The methodology based on geometric constraint and two-step error is simple and can rapidly calibrate the kinematic parameters of robot. It also leads to the improvement in the positioning accuracy of robot.

A distance error based industrial robot kinematic calibration method

2014 ◽  
Vol 41 (5) ◽  
pp. 439-446 ◽  
Author(s):  
Wang Zhenhua ◽  
Xu Hui ◽  
Chen Guodong ◽  
Sun Rongchuan ◽  
Lining Sun
Keyword(s):  
Industrial Robot ◽  
Calibration Method ◽  
Calibration Model ◽  
Kinematic Calibration ◽  
Absolute Position ◽  
Positioning Accuracy ◽  
Content Type ◽  
Distance Error ◽  
Position Accuracy ◽  
The Absolute

Purpose – The purpose of this paper is to present a distance accuracy-based industrial robot kinematic calibration model. Nowadays, the repeatability of the industrial robot is high, while the absolute positioning accuracy and distance accuracy are low. Many factors affect the absolute positioning accuracy and distance accuracy, and the calibration method of the industrial robot is an important factor. When the traditional calibration methods are applied on the industrial robot, the accumulative error will be involved according to the transformation between the measurement coordinate and the robot base coordinate. Design/methodology/approach – In this manuscript, a distance accuracy-based industrial robot kinematic calibration model is proposed. First, a simplified kinematic model of the robot by using the modified Denavit–Hartenberg (MDH) method is introduced, then the proposed distance error-based calibration model is presented; the experiment is set up in the next section. Findings – The experimental results show that the proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically. Originality/value – The proposed calibration model based on MDH and distance error can improve the distance accuracy and absolute position accuracy dramatically.

Positioning variation analysis and control for automated drilling in aircraft manufacturing

2018 ◽  
Vol 38 (4) ◽  
pp. 412-419 ◽  
Author(s):  
Biao Mei ◽  
Weidong Zhu ◽  
Yinglin Ke
Keyword(s):  
Vision System ◽  
Aviation Industry ◽  
Variation Analysis ◽  
Positioning Accuracy ◽  
Content Type ◽  
High Position ◽  
Position Errors ◽  
Aircraft Manufacturing ◽  
Drilling System ◽  
And Control

Purpose Aircraft assembly demands high position accuracy of drilled fastener holes. Automated drilling is a key technology to fulfill the requirement. The purpose of the paper is to conduct positioning variation analysis and control for an automated drilling to achieve a high positioning accuracy. Design/methodology/approach The nominal and varied connective models of automated drilling are constructed for positioning variation analysis regarding automated drilling. The principle of a strategy for reducing positioning variation in drilling, which shortens the positioning variation chain with the aid of an industrial camera-based vision system, is explored. Moreover, other strategies for positioning variation control are developed based on mathematical analysis to further reduce the position errors of the drilled fastener holes. Findings The propagation and accumulation of an automated drilling system’s positioning variation are explored. The principle of reducing positioning variation in an automated drilling using a monocular vision system is discussed from the view of variation chain. Practical implications The strategies for reducing positioning variation, rooted in the constructed positioning variation models, have been applied to a machine-tool based automated drilling system. The system is developed for a wing assembly of an aircraft in the Aviation Industry Corporation of China. Originality/value Propagation, accumulation and control of positioning variation in an automated drilling are comprehensively explored. Based on this, the positioning accuracy in an automated drilling is controlled below 0.13 mm, which can meet the requirement for the assembly of the aircraft.

scholarly journals Absolute Positioning Accuracy Improvement in an Industrial Robot

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4354 ◽  
Author(s):  
Yizhou Jiang ◽  
Liandong Yu ◽  
Huakun Jia ◽  
Huining Zhao ◽  
Haojie Xia
Keyword(s):  
Differential Evolution ◽  
Industrial Robot ◽  
Differential Evolution Algorithm ◽  
Substantial Improvement ◽  
Positioning Accuracy ◽  
Absolute Positioning ◽  
Calibration Methods ◽  
The Absolute ◽  
Six Degree Of Freedom ◽  
Kinematic Errors

The absolute positioning accuracy of a robot is an important specification that determines its performance, but it is affected by several error sources. Typical calibration methods only consider kinematic errors and neglect complex non-kinematic errors, thus limiting the absolute positioning accuracy. To further improve the absolute positioning accuracy, we propose an artificial neural network optimized by the differential evolution algorithm. Specifically, the structure and parameters of the network are iteratively updated by differential evolution to improve both accuracy and efficiency. Then, the absolute positioning deviation caused by kinematic and non-kinematic errors is compensated using the trained network. To verify the performance of the proposed network, the simulations and experiments are conducted using a six-degree-of-freedom robot and a laser tracker. The robot average positioning accuracy improved from 0.8497 mm before calibration to 0.0490 mm. The results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed network on an industrial robot.

scholarly journals Industrial Robot Vision System

1983 ◽  
Vol 16 (20) ◽  
pp. 337-341
Author(s):  
V.M. Grishkin ◽  
F.M. Kulakov
Keyword(s):  
Vision System ◽  
Industrial Robot ◽  
Robot Vision

The effects of materialism on consumer evaluation of sustainable synthetic (lab-grown) products

2020 ◽  
Vol 37 (5) ◽  
pp. 579-590
Author(s):  
Jessica Keech ◽  
Maureen Morrin ◽  
Jeffrey Steven Podoshen
Keyword(s):  
Design Methodology ◽  
Socially Responsible ◽  
Content Type ◽  
Consumer Evaluation ◽  
Positioning Strategy ◽  
Consumer Markets ◽  
The Future ◽  
Promotion Strategies ◽  
Alternative Sources ◽  
The Impact

Purpose The increasing desire of consumers for socially responsible luxury products combined with fluctuating supplies in consumer markets are leading various industries to seek alternative sources to be able to meet the needs of its customers. One possible solution that may meet the demands of the future is lab-grown products. Because these products confer multiple benefits, this study aims to investigate the most effective ways to appeal to consumers by aligning the benefits of the products with their values as marketers seek to find effective promotion for these items. Design/methodology/approach We examine the effectiveness of an ethical positioning strategy for two types of luxury lab-grown (synthetic) products among high versus low materialism consumers in three experiments. Findings Findings suggest that a positioning strategy stressing product ethicality is more effective for low materialism consumers, whereas the strategy is less effective, and may even backfire, for high materialism consumers. The impact on social status consumers perceive from a lab-grown product explains why this effect occurs among low materialism consumers. Therefore, marketers should take caution and use specific appeals for different segments based on values such as consumers’ materialism levels. Originality/value If lab-grown products represent the wave of the future, it is important to understand how consumers will respond to this emerging technology and how promotion strategies may enhance their evaluation.

The parameter identification model considering both geometric parameters and joint stiffness

2019 ◽  
Vol 47 (1) ◽  
pp. 76-81
Author(s):  
Jing Bai ◽  
Le Fan ◽  
Shuyang Zhang ◽  
Zengcui Wang ◽  
Xiansheng Qin
Keyword(s):  
Parameter Identification ◽  
Industrial Robot ◽  
Joint Stiffness ◽  
Geometric Parameters ◽  
Least Square ◽  
Experimental Result ◽  
Positional Accuracy ◽  
Content Type ◽  
The Absolute ◽  
Identification Model

Purpose Both geometric and non-geometric parameters have noticeable influence on the absolute positional accuracy of 6-dof articulated industrial robot. This paper aims to enhance it and improve the applicability in the field of flexible assembling processing and parts fabrication by developing a more practical parameter identification model. Design/methodology/approach The model is developed by considering both geometric parameters and joint stiffness; geometric parameters contain 27 parameters and the parallelism problem between axes 2 and 3 is involved by introducing a new parameter. The joint stiffness, as the non-geometric parameter considered in this paper, is considered by regarding the industrial robot as a rigid linkage and flexible joint model and adds six parameters. The model is formulated as the form of error via linearization. Findings The performance of the proposed model is validated by an experiment which is developed on KUKA KR500-3 robot. An experiment is implemented by measuring 20 positions in the work space of this robot, obtaining least-square solution of measured positions by the software MATLAB and comparing the result with the solution without considering joint stiffness. It illustrates that the identification model considering both joint stiffness and geometric parameters can modify the theoretical position of robots more accurately, where the error is within 0.5 mm in this case, and the volatility is also reduced. Originality/value A new parameter identification model is proposed and verified. According to the experimental result, the absolute positional accuracy can be remarkably enhanced and the stability of the results can be improved, which provide more accurate parameter identification for calibration and further application.

Human skill integrated motion planning of assembly manipulation for 6R industrial robot

2019 ◽  
Vol 46 (1) ◽  
pp. 171-180
Author(s):  
Yi Liu ◽  
Ming Cong ◽  
Hang Dong ◽  
Dong Liu
Keyword(s):  
Deep Learning ◽  
Motion Planning ◽  
Industrial Robot ◽  
Robotic Assembly ◽  
3D Vision ◽  
Content Type ◽  
Human Skill ◽  
Depth Images ◽  
Positioning Method ◽  
Assembly Technology

Purpose The purpose of this paper is to propose a new method based on three-dimensional (3D) vision technologies and human skill integrated deep learning to solve assembly positioning task such as peg-in-hole. Design/methodology/approach Hybrid camera configuration was used to provide the global and local views. Eye-in-hand mode guided the peg to be in contact with the hole plate using 3D vision in global view. When the peg was in contact with the workpiece surface, eye-to-hand mode provided the local view to accomplish peg-hole positioning based on trained CNN. Findings The results of assembly positioning experiments proved that the proposed method successfully distinguished the target hole from the other same size holes according to the CNN. The robot planned the motion according to the depth images and human skill guide line. The final positioning precision was good enough for the robot to carry out force controlled assembly. Practical implications The developed framework can have an important impact on robotic assembly positioning process, which combine with the existing force-guidance assembly technology as to build a whole set of autonomous assembly technology. Originality/value This paper proposed a new approach to the robotic assembly positioning based on 3D visual technologies and human skill integrated deep learning. Dual cameras swapping mode was used to provide visual feedback for the entire assembly motion planning process. The proposed workpiece positioning method provided an effective disturbance rejection, autonomous motion planning and increased overall performance with depth images feedback. The proposed peg-hole positioning method with human skill integrated provided the capability of target perceptual aliasing avoiding and successive motion decision for the robotic assembly manipulation.

The Pransky interview: Dr Yoky Matsuoka, Vice President Technology, Nest Labs

2014 ◽  
Vol 41 (6) ◽  
pp. 481-486
Author(s):  
Joanne Pransky
Keyword(s):  
Computer Science ◽  
Mechanical Engineering ◽  
Academic Career ◽  
Industrial Robot ◽  
Vice President ◽  
Early Career ◽  
Smoke Detector ◽  
Foundation Engineering ◽  
Content Type ◽  
The University

Purpose – This article is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry engineer-turned entrepreneur regarding the evolution, commercialization and challenges of bringing a technological invention to market. Design/methodology/approach – The interviewee is Dr Yoky Matsuoka, the Vice President of Nest Labs. Matsuoka describes her career journey that led her from a semi-professional tennis player who wanted to build a robot tennis buddy, to a pioneer of neurobotics who then applied her multidisciplinary research in academia to the development of a mass-produced intelligent home automation device. Findings – Dr Matsuoka received a BS degree from the University of California, Berkeley and an MS and PhD in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT). She was also a Postdoctoral Fellow in the Brain and Cognitive Sciences at MIT and in Mechanical Engineering at Harvard University. Dr Matsuoka was formerly the Torode Family Endowed Career Development Professor of Computer Science and Engineering at the University of Washington (UW), Director of the National Science Foundation Engineering Research Center for Sensorimotor Neural Engineering and Ana Loomis McCandless Professor of Robotics and Mechanical Engineering at Carnegie Mellon University. In 2010, she joined Google X as one of its three founding members. She then joined Nest as VP of Technology. Originality/value – Dr Matsuoka built advanced robotic prosthetic devices and designed complementary rehabilitation strategies that enhanced the mobility of people with manipulation disabilities. Her novel work has made significant scientific and engineering contributions in the combined fields of mechanical engineering, neuroscience, bioengineering, robotics and computer science. Dr Matsuoka was awarded a MacArthur Fellowship in which she used the Genius Award money to establish a nonprofit corporation, YokyWorks, to continue developing engineering solutions for humans with physical disabilities. Other awards include the Emerging Inventor of the Year, UW Medicine; IEEE Robotics and Automation Society Early Academic Career Award; Presidential Early Career Award for Scientists and Engineers; and numerous others. She leads the development of the learning and control technology for the Nest smoke detector and Thermostat, which has saved the USA hundreds of billions of dollars in energy expenses. Nest was sold to Google in 2013 for a record $3.2 billion dollars in cash.

scholarly journals Titan Cells Confer Protection from Phagocytosis in Cryptococcus neoformans Infections

2012 ◽  
Vol 11 (6) ◽  
pp. 820-826 ◽  
Author(s):  
Laura H. Okagaki ◽  
Kirsten Nielsen
Keyword(s):  
Cryptococcus Neoformans ◽  
Critical Role ◽  
Cell Formation ◽  
Pulmonary Cryptococcosis ◽  
Content Type ◽  
Cell Production ◽  
Human Fungal Pathogen ◽  
Large Size ◽  
Large Particles ◽  
The Relationship

ABSTRACTThe human fungal pathogenCryptococcus neoformansproduces an enlarged “titan” cell morphology when exposed to the host pulmonary environment. Titan cells exhibit traits that promote survival in the host. Previous studies showed that titan cells are not phagocytosed and that increased titan cell production in the lungs results in reduced phagocytosis of cryptococcal cells by host immune cells. Here, the effect of titan cell production on host-pathogen interactions during early stages of pulmonary cryptococcosis was explored. The relationship between titan cell production and phagocytosis was found to be nonlinear; moderate increases in titan cell production resulted in profound decreases in phagocytosis, with significant differences occurring within the first 24 h of the infection. Not only were titan cells themselves protected from phagocytosis, but titan cell formation also conferred protection from phagocytosis to normal-size cryptococcal cells. Large particles introduced into the lungs were not phagocytosed, suggesting the large size of titan cells protects against phagocytosis. The presence of large particles was unable to protect smaller particles from phagocytosis, revealing that titan cell size alone is not sufficient to provide the observed cross-protection of normal-size cryptococcal cells. These data suggest that titan cells play a critical role in establishment of the pulmonary infection by promoting the survival of the entire population of cryptococcal cells.

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