Trajectory Control for Robotic Arc Welding Applications

1996 ◽  
Author(s):  
Tuna Balkan
Keyword(s):  
Arc Welding ◽  
Control Algorithm ◽  
Vision System ◽  
Industrial Robot ◽  
Robotic Welding ◽  
Closed Loop System ◽  
Robotic Arc Welding ◽  
Performance Curves ◽  
Typical Performance ◽  
Joint Variable

Abstract In this study, a PC based program is developed for robotic welding applications. This program includes synthetic generation of Cartesian trajectories based on prespecified points on the trajectory and predetermined velocity profile. Such points can be provided in the teach mode or by using a vision system assisted by a special algorithm. The control algorithm is based on the measurement of joint variable positions and rates resulting in a closed-loop system with a model-based part. These algorithms are applied to an industrial robot performing arc welding weaving applications and typical performance curves are obtained under simulated conditions.

scholarly journals A real-time passive vision system for robotic arc welding

2015 ◽  
Author(s):  
Jinchao Liu ◽  
Zhun Fan ◽  
Soren Ingvor Olsen ◽  
Kim Hardam Christensen ◽  
Jens Klastrup Kristensen
Keyword(s):  
Real Time ◽  
Arc Welding ◽  
Vision System ◽  
Robotic Arc Welding

Machine Vision Analysis of Welding Region and its Application to Seam Tracking in Arc Welding

1993 ◽  
Vol 207 (4) ◽  
pp. 275-283 ◽  
Author(s):  
Y Li ◽  
J E Middle
Keyword(s):  
Machine Vision ◽  
Arc Welding ◽  
Vision System ◽  
Low Cost ◽  
Gas Metal Arc Welding ◽  
Seam Tracking ◽  
Optical Parameters ◽  
Robotic Welding ◽  
Radiated Energy ◽  
Welding Processes

Unlike the application of machine vision in many other fields, there is a particular problem in developing machine vision for automated and robotic welding processes, because the disturbance of the arc light deteriorates the field to be viewed. This paper describes an analysis of the radiated energy from the weld pool, and based on this describes how vision sensing of the welding region may be improved. An approach using specified pattern parameters is described to evaluate the ability to recognize an acquired image under different conditions such as with vidicons or sensor devices, different welding variables and optical parameters. Based on analysis of radiation from the welding region, a satisfactory wavelength range for sensing the image of the weld region is proposed and proved by experimentation. Images of gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) regions have been modelled and successfully implemented for seam tracking control with a simultaneously developed low-cost vision system.

scholarly journals Detection Method of Welding Defects in a Robotic Station Using the Deep Neural Network

2021 ◽  
Vol 25 (1) ◽  
pp. 67-72
Author(s):  
Arkadiusz Adamczak
Keyword(s):  
Neural Network ◽  
Arc Welding ◽  
Deep Neural Network ◽  
Deep Neural Networks ◽  
Weld Seam ◽  
Detection Method ◽  
Vision System ◽  
Industrial Robot ◽  
Welding Defects ◽  
Basic Quality

Modern automation and robotization of production processes requires new and fast methods of product quality control. In the case of arc welding in robotic systems, where the production process takes place in large series, it is important to quickly control the correctness of the weld. Based on visual data, the system should be able to automatically determine whether a given weld meets the basic quality requirements, and thus be able to stop the process in the event of identified defects. The article presents the results of research on the creation of a visual method for assessing the correctness of the weld seam based on the deep neural network classifying, locating and segmenting welding defects. The proposed detection method was extended by using a combination of a vision system camera with a six-axis industrial robot in order to enable detection of a larger number of welding defects and positioning in a six-dimensional workspace. The research results presented in this article were obtained during the implementation of the project entitled „Development of a method based on the use of deep neural networks for visual inspection of welded joints in the course of R&D works” implemented at the company ZAP-Robotyka Sp. z o.o. in Ostrów Wielkopolski.

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 research on visual industrial robot which adopts fuzzy PID control algorithm

2017 ◽  
Author(s):  
Yifei Feng ◽  
Guoping Lu ◽  
Lulin Yue ◽  
Weifeng Jiang ◽  
Ye Zhang
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Industrial Robot ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control

A Digital Algorithm for Near-Minimum-Time Control of Robot Manipulators

1987 ◽  
Vol 109 (4) ◽  
pp. 320-327 ◽  
Author(s):  
C. K. Kao ◽  
A. Sinha ◽  
A. K. Mahalanabis
Keyword(s):  
Control Algorithm ◽  
State Feedback ◽  
Closed Loop ◽  
Robot Manipulator ◽  
Minimum Time ◽  
State Feedback Control ◽  
Final States ◽  
Closed Loop System ◽  
Time Control ◽  
Digital Algorithm

A digital state feedback control algorithm has been developed to obtain the near-minimum-time trajectory for the end-effector of a robot manipulator. In this algorithm, the poles of the linearized closed loop system are judiciously placed in the Z-plane to permit near-minimum-time response without violating the constraints on the actuator torques. The validity of this algorithm has been established using numerical simulations. A three-link manipulator is chosen for this purpose and the results are discussed for three different combinations of initial and final states.

Analysis of Five-Degree-of-Freedom Robot Arms

1983 ◽  
Vol 105 (1) ◽  
pp. 23-27 ◽  
Author(s):  
K. Sugimoto ◽  
J. Duffy
Keyword(s):  
Arc Welding ◽  
Degrees Of Freedom ◽  
Screw Theory ◽  
Industrial Robot ◽  
Degree Of Freedom ◽  
Numerical Example ◽  
Robot Arms ◽  
Special Cases ◽  
Computer Controlled ◽  
Five Axes

Many kinds of robot arms with five degrees of freedom are widely used in industry for arc welding, spray painting, assembling etc. It is necessary to be able to compute joint displacements when such devices are computer controlled. A solution to this problem is presented and the analysis is illustrated by a numerical example using the most common industrial robot with five axes. Further, special cases are discussed using screw theory.

Modelling functioning of an adaptive industrial robot in arc welding

2000 ◽  
Vol 14 (1) ◽  
pp. 60-63
Author(s):  
V G Nuzhdikhin ◽  
V K Borisov ◽  
D P limarenko
Keyword(s):  
Arc Welding ◽  
Industrial Robot
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