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.

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.

Kalman Filter-Based Robot Manipulator Five-Degrees of Freedom Uncalibrated Vision Positioning

2014 ◽  
Vol 668-669 ◽  
pp. 347-351 ◽  
Author(s):  
Lang Liu ◽  
Niu Wang ◽  
Chu Zhong Yu ◽  
Da Tao Wang
Keyword(s):  
Kalman Filter ◽  
Visual Servoing ◽  
Degrees Of Freedom ◽  
Robot Manipulator ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Image Features ◽  
Image Space ◽  
Online Estimation ◽  
Vision Positioning

Robot manipulator position and posture control is a popular topic in the field of uncalibrated visual servoing, this paper presents a kalman filter-based robot manipulator five-degrees of freedom uncalibrated vision positioning method. In the case of the fixed binocular cameras and manipulator parameters are unknown; firstly, the specific point and angle image features information in the camera image space were selected in order to describe the relative pose relationship between robot manipulator ends and goals. Then, the kalman filter online estimation algorithm was applied to calculate image Jacobian matrix which is mapping relationship between image space to cartesian mission space, and vision controller was designed in the image plane realized robot manipulator five-degrees of freedom uncalibrated vision positioning control. Finally, Six-degrees of freedom robot manipulator’s five-degrees of freedom uncalibrated visual positioning Simulink model established in the Matlab environment, and the simulation result show that kalman filter online estimation method made the robot manipulator rapid convergence to the desired position and posture with high accuracy.

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 Students’ Understanding on Formal Definition of Limit

2021 ◽  
Vol 1752 (1) ◽  
pp. 012082
Author(s):  
Nurdin ◽  
S F Assagaf ◽  
F Arwadi
Keyword(s):  
Formal Definition ◽  
Definition Of

Diagnosis Rule Discovery Based on Causality in the Context of Fault Diagnosis in Rotating Machinery

2014 ◽  
Vol 532 ◽  
pp. 113-117
Author(s):  
Zhou Jin ◽  
Ru Jing Wang ◽  
Jie Zhang
Keyword(s):  
Fault Diagnosis ◽  
General Framework ◽  
Complex Structure ◽  
Rotating Machinery ◽  
Massive Data ◽  
Formal Definition ◽  
Rule Discovery ◽  
Rule Based ◽  
Simple Implementation ◽  
Definition Of

The rotating machineries in a factory usually have the characteristics of complex structure and highly automated logic, which generated a large amounts of monitoring data. It is an infeasible task for uses to deal with the massive data and locate fault timely. In this paper, we explore the causality between symptom and fault in the context of fault diagnosis in rotating machinery. We introduce data mining into fault diagnosis and provide a formal definition of causal diagnosis rule based on statistic test. A general framework for diagnosis rule discovery based on causality is provided and a simple implementation is explored with the purpose of providing some enlightenment to the application of causality discovery in fault diagnosis of rotating machinery.

scholarly journals Time to Harmonize Dengue Nomenclature and Classification

Viruses ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 569 ◽  
Author(s):  
Lize Cuypers ◽  
Pieter Libin ◽  
Peter Simmonds ◽  
Ann Nowé ◽  
Jorge Muñoz-Jordán ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Dengue Virus ◽  
Classification System ◽  
Formal Definition ◽  
Classification Procedure ◽  
Genotype 2 ◽  
Global Spread ◽  
Significant Burden ◽  
Definition Of ◽  
Epidemiological Characteristics

Dengue virus (DENV) is estimated to cause 390 million infections per year worldwide. A quarter of these infections manifest clinically and are associated with a morbidity and mortality that put a significant burden on the affected regions. Reports of increased frequency, intensity, and extended geographical range of outbreaks highlight the virus’s ongoing global spread. Persistent transmission in endemic areas and the emergence in territories formerly devoid of transmission have shaped DENV’s current genetic diversity and divergence. This genetic layout is hierarchically organized in serotypes, genotypes, and sub-genotypic clades. While serotypes are well defined, the genotype nomenclature and classification system lack consistency, which complicates a broader analysis of their clinical and epidemiological characteristics. We identify five key challenges: (1) Currently, there is no formal definition of a DENV genotype; (2) Two different nomenclature systems are used in parallel, which causes significant confusion; (3) A standardized classification procedure is lacking so far; (4) No formal definition of sub-genotypic clades is in place; (5) There is no consensus on how to report antigenic diversity. Therefore, we believe that the time is right to re-evaluate DENV genetic diversity in an essential effort to provide harmonization across DENV studies.

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