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.

Robust industrial robot real-time positioning system using VW-camera-space manipulation method

2014 ◽  
Vol 41 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Yong Liu ◽  
Dingbing Shi ◽  
Steven Baard Skaar
Keyword(s):  
Real Time ◽  
Camera Calibration ◽  
Industrial Robot ◽  
Research Problem ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Positioning System ◽  
Content Type ◽  
Time Performance ◽  
The Impact

Purpose – Vision-based positioning without camera calibration, using uncalibrated industrial robots, is a challenging research problem. To address the issue, an uncalibrated industrial robot real-time positioning system has been developed in this paper. The paper aims to discuss these issues. Design/methodology/approach – The software and hardware of this system as well as the methodology are described. Direct and inverse kinematics equations that map joint space into “camera space” are developed. The camera-space manipulation (CSM) algorithm has been employed and improved with varying weights on camera samples of the robot end effector, and the improved CSM is named VW-CSM. The experiments of robot positioning have been conducted using the traditional CSM algorithm and the varying-weight CSM (VW-CSM) algorithm, respectively, both without separate camera calibration. The impact on the accuracy and real-time performance of the system caused by different weights has been examined and discussed. Findings – The experimental results show that the accuracy and real-time performance of the system with the VW-CSM algorithm is better than the one with using the original CSM algorithm, and the impact on the accuracy and real-time performance of the system caused by different weights has been revealed. Originality/value – The accuracy and real-time performance of the system with the VW-CSM algorithm is verified. These results prove that the developed system using the VW-CSM algorithm can satisfy the requirements of most industrial applications and can be widely used in the field of industrial robots.

Concepts of Augmented Image Space and Transformed Feature Space for Efficient Visual Servoing of an “Eye-in-Hand Robot”

Robotica ◽  
1991 ◽  
Vol 9 (2) ◽  
pp. 203-212 ◽  
Author(s):  
Won Jang ◽  
Kyungjin Kim ◽  
Myungjin Chung ◽  
Zeungnam Bien
Keyword(s):  
Visual Feedback ◽  
Visual Servoing ◽  
Industrial Robot ◽  
Robot Vision ◽  
Feature Space ◽  
Image Features ◽  
Image Space ◽  
Formal Definition ◽  
Computational Burden ◽  
Definition Of

SUMMARYFor efficient visual servoing of an “eye-in-hand” robot, the concepts of Augmented Image Space and Transformed Feature Space are presented in the paper. A formal definition of image features as functionals is given along with a technique to use defined image features for visual servoing. Compared with other known methods, the proposed concepts reduce the computational burden for visual feedback, and enhance the flexibility in describing the vision-based task. Simulations and real experiments demonstrate that the proposed concepts are useful and versatile tools for the industrial robot vision tasks, and thus the visual servoing problem can be dealt with more systematically.

scholarly journals Interactive, Collaborative Robots: Challenges and Opportunities

2018 ◽  
Author(s):  
Danica Kragic ◽  
Joakim Gustafson ◽  
Hakan Karaoguz ◽  
Patric Jensfelt ◽  
Robert Krug
Keyword(s):  
Manufacturing Industry ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Service Robots ◽  
Natural Interaction ◽  
Current State ◽  
Challenges And Opportunities ◽  
Important Open Problem ◽  
In The Beginning ◽  
Office Environments

Robotic technology has transformed manufacturing industry ever since the first industrial robot was put in use in the beginning of the 60s. The challenge of developing flexible solutions where production lines can be quickly re-planned, adapted and structured for new or slightly changed products is still an important open problem. Industrial robots today are still largely preprogrammed for their tasks, not able to detect errors in their own performance or to robustly interact with a complex environment and a human worker. The challenges are even more serious when it comes to various types of service robots. Full robot autonomy, including natural interaction, learning from and with human, safe and flexible performance for challenging tasks in unstructured environments will remain out of reach for the foreseeable future. In the envisioned future factory setups, home and office environments, humans and robots will share the same workspace and perform different object manipulation tasks in a collaborative manner. We discuss some of the major challenges of developing such systems and provide examples of the current state of the art.

Adaptive Industrial Robots Using Machine Vision

2018 ◽  
Author(s):  
Vladimir Kuts ◽  
Tauno Otto ◽  
Toivo Tähemaa ◽  
Khuldoon Bukhari ◽  
Tengiz Pataraia
Keyword(s):  
Machine Vision ◽  
Manufacturing Industry ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Engineering Industry ◽  
Test Environment ◽  
Operation System ◽  
Robotic Cells ◽  
Self Learning ◽  
Human Robot Collaboration

The use of industrial robots in modern manufacturing scenarios is a rising trend in the engineering industry. Currently, industrial robots are able to perform pre-programmed tasks very efficiently irrespective of time and complexity. However, often robots encounter unknown scenarios and to solve those, they need to cooperate with humans, leading to unnecessary downtime of the machine and the need for human intervention. The main aim of this study is to propose a method to develop adaptive industrial robots using Machine Learning (ML)/Machine Vision (MV) tools. The proposed method aims to reduce the effort of re-programming and enable self-learning in industrial robots. The elaborated online programming method can lead to fully automated industrial robotic cells in accordance with the human-robot collaboration standard and provide multiple usage options of this approach in the manufacturing industry. Machine Vision (MV) tools used for online programming allow industrial robots to make autonomous decisions during sorting or assembling operations based on the color and/or shape of the test object. The test setup consisted of an industrial robot cell, cameras and LIDAR connected to MATLAB through a Robot Operation System (ROS). The online programming tests and simulations were performed using Virtual/Augmented Reality (VR/AR) toolkits together with a Digital Twin (DT) concept, to test the industrial robot program on a digital object before executing it on the real object, thus creating a safe and secure test environment.

MACHINE VISION 1992–1996, TECHNOLOGY PROGRAM IN FINLAND

1996 ◽  
Vol 10 (01) ◽  
pp. 3-13 ◽  
Author(s):  
ANTTI J. SOINI
Keyword(s):  
Machine Vision ◽  
Manufacturing Industry ◽  
Technology Development ◽  
New Technology ◽  
Robot Vision ◽  
Industrial Applications ◽  
Technology Program ◽  
Research Organizations ◽  
Innovative Products ◽  
New Business

Machine vision technology has attracted a strong interest among Finnish research organizations, which has resulted in many innovative products for industry. Despite this goal users were very skeptical towards machine vision and its robustness in harsh industrial environments. Therefore the Technology Development Centre, TEKES, which funds technology related research and development projects in universities and individual companies in Finland, decided to start a national technology program, "Machine Vision 1992–1996". Led by industry, the program boosts research in machine vision technology and seeks to put the research results to work in practical industrial applications. The emphasis is on nationally important, demanding applications. The program will create new business for machine vision producers and encourage the process and manufacturing industry to take advantage of this new technology. So far 60 companies and all major universities and research centers in Finland are working on our forty different projects. The key themes are Process Control, Robot Vision and Quality Control.

HIGH-SPEED INDUSTRIAL REAL-TIME NETWORK OF CYBERPHYSICAL SYSTEMS

2019 ◽  
pp. 46-52
Author(s):  
A. A. Zelensky
Keyword(s):  
Real Time ◽  
Cycle Time ◽  
High Speed ◽  
High Efficiency ◽  
Industrial Robot ◽  
Field Tests ◽  
Industrial Robots ◽  
Third Party ◽  
Industrial Equipment ◽  
Industrial Automation

The construction of a high-speed industrial real-time network based on FPGA (Field-Programmable Gate Array) for the control of machines and industrial robots is considered. A brief comparative analysis of the performance of the implemented Ethernet-based Protocol with industrial protocols of other leading manufacturers is made. The aim of the research and development of its own industrial automation Protocol was to reduce the dependence on third-party real-time protocols based on Ethernet for controlling robots, machines and technological equipment. In the course of the study, the requirements for the network of the motion control system of industrial equipment were analyzed. In order to synchronize different network nodes and provide short exchange cycle time, an industrial managed switch was developed, as well as a specialized hardware controller for processing Ethernet packets for end devices, presented as a IP-core. A key feature of the developed industrial network is that the data transmission in it is completely determined, and the exchange cycle time for each of the network devices can be configured individually. High efficiency and performance of implemented network devices became possible due to the use of hardware solutions based on FPGAs. All solutions described in the article as part of a modular digital system have been successfully tested in the control of machines and industrial robot. The results of field tests show that the use of FPGAs and soft processors with specialized peripheral IP-blocks can significantly reduce the tact of managing industrial equipment through the use of hardware computing structures, which indicates the promise of the proposed approach for solving industrial automation tasks.

Control System Design for High Payload Industrial Robot via High Speed Communication Bus and Real-Time System

2011 ◽  
Vol 464 ◽  
pp. 272-278 ◽  
Author(s):  
Wei You ◽  
Min Xiu Kong ◽  
Li Ning Sun ◽  
Chan Chan Guo
Keyword(s):  
Control System ◽  
Real Time ◽  
High Speed ◽  
Industrial Robot ◽  
Engineering Application ◽  
Industrial Robots ◽  
Centralized Control ◽  
Time System ◽  
Real Time System ◽  
High Payload

In this paper, aiming at solving the problems of dynamic coupling effects and flexibility of joints and links, a kind of control system specialized for high payload industrial robots is proposed . After the comparisons between the control systems in all kinds of robots and numerical machines, industrial PC with TwinCAT real-time system is chosen as the motion control unit, EtherCAT is used for command transmitting. The whole control system has a decoupled and centralized control structure. The proposed control system is applied in control of a kind of high payload material handling robots with complex compound control algorithms. The final results shows that the control commands can be easily calculated and transmitted in one sample unit. The proposed control scheme is meaningful to real engineering application.

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.

NEURAL NETWORK BASED DYNAMIC CONTROLLERS FOR INDUSTRIAL ROBOTS

1995 ◽  
Vol 06 (03) ◽  
pp. 257-271
Author(s):  
SE-YOUNG OH ◽  
WEON-CHANG SHIN ◽  
HYO-GYU KIM
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Network Architecture ◽  
Industrial Robot ◽  
Industrial Robots ◽  
System Stability ◽  
Robot Dynamics ◽  
Time Dynamic ◽  
Dynamic Controller ◽  
And Control

The industrial robot’s dynamic performance is frequently measured by positioning accuracy at high speeds and a good dynamic controller is essential that can accurately compute robot dynamics at a servo rate high enough to ensure system stability. A real-time dynamic controller for an industrial robot is developed here using neural networks. First, an efficient time-selectable hidden layer architecture has been developed based on system dynamics localized in time, which lends itself to real-time learning and control along with enhanced mapping accuracy. Second, the neural network architecture has also been specially tuned to accommodate servo dynamics. This not only facilitates the system design through reduced sensing requirements for the controller but also enhances the control performance over the control architecture neglecting servo dynamics. Experimental results demonstrate the controller’s excellent learning and control performances compared with a conventional controller and thus has good potential for practical use in industrial robots.

scholarly journals Development Status and Trend of Industrial Robot in China

2021 ◽  
Vol 5 (2) ◽  
pp. p49
Author(s):  
Gao Hang
Keyword(s):  
Artificial Intelligence ◽  
Manufacturing Industry ◽  
Industrial Robot ◽  
Development Trend ◽  
Industrial Robots ◽  
Continuous Development ◽  
Industrial Robotics ◽  
Development Status ◽  
The World ◽  
The Times

With the continuous development of the times, technology is flourishing and the world is entering the era of artificial intelligence, industrial robots will replace humans as the backbone of the manufacturing industry. The continuous development and application of industrial robotics is conducive to building a new advantage for China’s manufacturing, promoting the transformation and upgrading of China’s industry, accelerating the construction of China’s manufacturing power, and making an important contribution to China’s economic development. Based on this, the article describes the current situation of industrial robots in China, the challenges faced, and the future development trend.

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