scholarly journals Intelligent Perception System of Robot Visual Servo for Complex Industrial Environment

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7121
Author(s):  
Yongchao Luo ◽  
Shipeng Li ◽  
Di Li
Keyword(s):  
Visual Information ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Region Of Interest ◽  
Servo System ◽  
Experimental Result ◽  
Visual Servo ◽  
Industrial Environment ◽  
Perception System

Robot control based on visual information perception is a hot topic in the industrial robot domain and makes robots capable of doing more things in a complex environment. However, complex visual background in an industrial environment brings great difficulties in recognizing the target image, especially when a target is small or far from the sensor. Therefore, target recognition is the first problem that should be addressed in a visual servo system. This paper considers common complex constraints in industrial environments and proposes a You Only Look Once Version 2 Region of Interest (YOLO-v2-ROI) neural network image processing algorithm based on machine learning. The proposed algorithm combines the advantages of YOLO (You Only Look Once) rapid detection with effective identification of ROI (Region of Interest) pooling structure, which can quickly locate and identify different objects in different fields of view. This method can also lead the robot vision system to recognize and classify a target object automatically, improve robot vision system efficiency, avoid blind movement, and reduce the calculation load. The proposed algorithm is verified by experiments. The experimental result shows that the learning algorithm constructed in this paper has real-time image-detection speed and demonstrates strong adaptability and recognition ability when processing images with complex backgrounds, such as different backgrounds, lighting, or perspectives. In addition, this algorithm can also effectively identify and locate visual targets, which improves the environmental adaptability of a visual servo system

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

scholarly journals 3D Robot Vision System through 2D Shape Based Matching Using Gaussian Smoothing for Gluing Application

2018 ◽  
Vol 7 (4.33) ◽  
pp. 487
Author(s):  
Mohamad Haniff Harun ◽  
Mohd Shahrieel Mohd Aras ◽  
Mohd Firdaus Mohd Ab Halim ◽  
Khalil Azha Mohd Annuar ◽  
Arman Hadi Azahar ◽  
...  
Keyword(s):  
Template Matching ◽  
Shape Matching ◽  
Vision System ◽  
Recognition Rate ◽  
Three Dimensional ◽  
Robot Vision ◽  
Region Of Interest ◽  
Gaussian Smoothing ◽  
Detection Approach ◽  
Vision Algorithm

This investigation is solely on the adaptation of a vision system algorithm to classify the processes to regulate the decision making related to the tasks and defect’s recognition. These idea stresses on the new method on vision algorithm which is focusing on the shape matching properties to classify defects occur on the product. The problem faced before that the system required to process broad data acquired from the object caused the time and efficiency slightly decrease. The propose defect detection approach combine with Region of Interest, Gaussian smoothing, Correlation and Template Matching are introduced. This application provides high computational savings and results in better recognition rate about 95.14%. The defects occur provides with information of the height which corresponds by the z-coordinate, length which corresponds by the y-coordinate and width which corresponds by the x-coordinate. This data gathered from the proposed system using dual camera for executing the three dimensional transformation.  

Target Location of Industrial Robot Based on Vision

2014 ◽  
Vol 945-949 ◽  
pp. 1478-1481
Author(s):  
Gui Hong Jia
Keyword(s):  
Target Location ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Contour Extraction ◽  
Multiple Target ◽  
Segmentation Method ◽  
Target Image ◽  
Black And White ◽  
Centroid Position

Vision is the most important way to obtain information from the word. This paper collected the target image using industrial robot vision system, and We get Black and white images using binary image segmentation method, then the contour of each object in the image can be obtained with edge detection and contour extraction, The centroid position was confirmed using minimum enclosing rectangle method after gaining the outline of target. The experimental results show that this method can quickly and accurately obtain multiple target centroid position.

scholarly journals A Vision Calibration Method of Robot based on Halcon

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Calibration Method ◽  
System Calibration ◽  
Radial Distortion ◽  
Vision Control ◽  
Calibration Accuracy ◽  
The Relationship ◽  
Research Hotspots

Visual calibration is an important researchdirection in the field of robot vision control, and is also one of thecurrent research hotspots. In this paper, the principle of softwarecalibration is described in detail, and a software calibrationmethod based on Halcon optimization is studied and designed. Byusing the operator in the function library, the internal andexternal parameters of the camera are calibrated. The influence ofthe terminal center of the robot and the radial distortion of thecamera lens is fully considered. The method is used to establish thecamera. The relationship between the image coordinated systemand the robot world coordinated system. Experiments show thatthe method has high calibration accuracy and practicability, andis suitable for industrial robot vision system calibration.

The Research on the Robot Vision System Based on the Target Clamping Technology

2012 ◽  
Vol 430-432 ◽  
pp. 1929-1934
Author(s):  
Huai Xing Wen ◽  
Wen Sheng Wang
Keyword(s):  
Visual Recognition ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Target Object ◽  
Recognition Algorithms

Introduces the structure and the components of industrial robot vision system. Through designing the gripping point, the location of the clamping point can be planned out in the clamping operation, and then by visual recognition algorithms to calculate the coordinate figure of the clamping point relative to the camera. Then the calculated values would transmitted to computer, by whose control of the robot’s move can the operation of clamping on the target object be achieved.

Combined force and visual control of an industrial robot

Robotica ◽  
2004 ◽  
Vol 22 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Ricardo Carelli ◽  
Eduardo Oliva ◽  
Carlos Soria ◽  
Oscar Nasisi
Keyword(s):  
Force Control ◽  
Visual Information ◽  
Visual Servoing ◽  
Force Feedback ◽  
Hybrid Control ◽  
Industrial Robot ◽  
Servo Control ◽  
Visual Servo ◽  
Control Structures ◽  
Vision Servo

This work proposes control structures that efficiently combine force control with vision servo control of robot manipulators. Impedance controllers are considered which are based both on visual servoing and on physical or fictitious force feedback, the force and visual information being combined in the image space. Force and visual servo controllers included in extended hybrid control structures are also considered. The combination of both force and vision based control allows the tasks range of the robot to be extended to partially structured environments. The proposed controllers, implemented on an industrial SCARA-type robot, are tested in tasks involving physical and virtual contact with the environment.

TOWARDS GRASP-ORIENTED VISUAL PERCEPTION FOR HUMANOID ROBOTS

2009 ◽  
Vol 06 (03) ◽  
pp. 387-434 ◽  
Author(s):  
JEANNETTE BOHG ◽  
CARL BARCK-HOLST ◽  
KAI HUEBNER ◽  
MARIA RALPH ◽  
BABAK RASOLZADEH ◽  
...  
Keyword(s):  
Visual Information ◽  
State Of The Art ◽  
Vision System ◽  
Robot Vision ◽  
Humanoid Robots ◽  
Specific Context ◽  
Reasoning System ◽  
Different Types ◽  
Distinct Property ◽  
Perception Action

A distinct property of robot vision systems is that they are embodied. Visual information is extracted for the purpose of moving in and interacting with the environment. Thus, different types of perception-action cycles need to be implemented and evaluated. In this paper, we study the problem of designing a vision system for the purpose of object grasping in everyday environments. This vision system is firstly targeted at the interaction with the world through recognition and grasping of objects and secondly at being an interface for the reasoning and planning module to the real world. The latter provides the vision system with a certain task that drives it and defines a specific context, i.e. search for or identify a certain object and analyze it for potential later manipulation. We deal with cases of: (i) known objects, (ii) objects similar to already known objects, and (iii) unknown objects. The perception-action cycle is connected to the reasoning system based on the idea of affordances. All three cases are also related to the state of the art and the terminology in the neuroscientific area.

Embedded Robot Vision System Based on DSP

2015 ◽  
Vol 734 ◽  
pp. 168-171
Author(s):  
Xing Ze Li ◽  
Ling Zhu ◽  
Yi Hua
Keyword(s):  
System Design ◽  
Real Time ◽  
Robot Control ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Ccd Camera ◽  
Target Object ◽  
The Real ◽  
Time Problem

Aim at the real-time problem of industrial robot vision system, design a embedded robot vision system based on DSP microprocessor. This system can use CCD camera and the ultrasonic sensor to collect the target environment information. It also can use the processor DSP to process the images and recognize target. And then through the communication module, send results in the form of wireless to the upper computer, providing target object information for robot control layer. This system completes the software and hardware system design, image collection & processing and robot control, as well as meet the real-time requirements of machine vision system.

Developments in Visual Servoing for Mobile Manipulation

2013 ◽  
Vol 01 (01) ◽  
pp. 143-162 ◽  
Author(s):  
Haoxiang Lang ◽  
Muhammad Tahir Khan ◽  
Kok-Kiong Tan ◽  
Clarence W. de Silva
Keyword(s):  
Visual Information ◽  
Visual Servoing ◽  
Mobile Robotics ◽  
Servo System ◽  
General Concept ◽  
Mobile Manipulation ◽  
Visual Servo ◽  
Servo Systems ◽  
Manipulation System ◽  
Fixed Base

A new trend in mobile robotics is to integrate visual information in feedback control for facilitating autonomous grasping and manipulation. The result is a visual servo system, which is quite beneficial in autonomous mobile manipulation. In view of mobility, it has wider application than the traditional visual servoing in manipulators with fixed base. In this paper, the state of art of vision-guided robotic applications is presented along with the associated hardware. Next, two classical approaches of visual servoing: image-based visual servoing (IBVS) and position-based visual servoing (PBVS) are reviewed; and their advantages and drawbacks in applying to a mobile manipulation system are discussed. A general concept of modeling a visual servo system is demonstrated. Some challenges in developing visual servo systems are discussed. Finally, a practical application of mobile manipulation system which is developed for applications of search and rescue and homecare robotics is introduced.

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