Stereo Image Ranging For An Autonomous Robot Vision System

1985 ◽  
Author(s):  
James R. Holten III ◽  
Steven K. Rogers ◽  
Matthew Kabrisky ◽  
Steven Cross
Keyword(s):  
Vision System ◽  
Robot Vision ◽  
Autonomous Robot ◽  
Stereo Image

Conceptual space as a connection between the constructivist and the ecological approaches in a robot vision system

2002 ◽  
Vol 25 (1) ◽  
pp. 100-101
Author(s):  
Antonio Chella
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Robot Vision ◽  
Autonomous Robot ◽  
Conceptual Space ◽  
Ecological Vision ◽  
Representation Structure

The conceptual space< (Gärdenfors 2000) is discussed as a representation structure that connects the constructivist and the ecological vision subsystems in an operating autonomous robot based on computer vision.

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

A Robot Vision System Based on Two-Dimensional Object-Oriented Models

1986 ◽  
Vol 16 (4) ◽  
pp. 582-589 ◽  
Author(s):  
Lorenz A. Schmitt ◽  
William A. Gruver ◽  
Assad Ansari
Keyword(s):  
Vision System ◽  
Robot Vision ◽  
Object Oriented ◽  
Two Dimensional ◽  
Dimensional Object

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.  

The PUMA/VS-100 Robot Vision System

Robot Vision ◽  
1983 ◽  
pp. 313-323 ◽  
Author(s):  
Brian Carlisle ◽  
Scot Roth
Keyword(s):  
Vision System ◽  
Robot Vision
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