Cognitive Robotics. Development of depalletizing robot vision system using stereo vision with random dot pattern proJection.

Calibration is essential for any robot vision system for achieving high accuracy in deriving objects metric information. One of typical requirements for a stereo vison system in order to obtain better calibration results is to guarantee that both cameras keep the same vertical level. However, cameras may be displaced due to severe conditions of a robot operating or some other circumstances. This paper presents our experimental approach to the problem of a mobile robot stereo vision system calibration under a hardware imperfection. In our experiments, we used crawler-type mobile robot «Servosila Engineer». Stereo system cameras of the robot were displaced relative to each other, causing loss of surrounding environment information. We implemented and verified checkerboard and circle grid based calibration methods. The two methods comparison demonstrated that a circle grid based calibration should be preferred over a classical checkerboard calibration approach.

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Research on the Visual Recognition Algorithm for Loading Robot Vision System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.271-272.1645 ◽

2012 ◽

Vol 271-272 ◽

pp. 1645-1648

Author(s):

Yong Tao Yang ◽

Huai Xing Wen

Keyword(s):

Approximation Algorithm ◽

Stereo Vision ◽

Visual Recognition ◽

Object Segmentation ◽

Vision System ◽

Robot Vision ◽

Target Object ◽

Recognition Algorithm ◽

Binocular Stereo Vision ◽

Binocular Stereo

In order to study the questions about the recognition of relative position for the operating object and calculation of the object volume in the loading robot binocular stereo vision system. Based on the characteristics of the operating object, proposed the method that use of its vertices only to match the corresponding point of the camera imaging for location identification, also raised the approximation algorithm that firstly, cut up the whole, followed by calculate the volume of the various parts, then carry out the sum of the each segmentation volume. Experiments and analysis showed that the distance of camera and the object greater affect the visual system, less impact on the intensity of light；In the target object segmentation， the number of partition k=11 is better. Both methods produced the small errors for the visual recognition of the system, it can meet actual needs.

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Mechanical Robot Vision Image Segmentation Using Chaos-Particle Swarm Optimization Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.574.511 ◽

2014 ◽

Vol 574 ◽

pp. 511-516

Author(s):

Hai Bo Liu ◽

Su Yan Zhang ◽

Yu Mei Wang

Keyword(s):

Particle Swarm Optimization ◽

Image Segmentation ◽

Stereo Vision ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Vision System ◽

Robot Vision ◽

Swarm Optimization ◽

Binocular Stereo Vision ◽

Binocular Stereo

The image segmentation of a robot binocular stereo vision system is the key issue in imaging processing. In this paper, the method of 2-D maximum entropy threshold image segmentation with chaos-particle swarm optimization algorithm is used to segment the images information collected by a robot vision system, and the algorithm is checked by a real robot binocular stereo vision system. The results show that more space information of an image is sufficiently used by the above method, and the running time is shortened by the algorithm. In addition, the image segmentation effect is better than other conventional methods.

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THE SURREY ATTENTIVE ROBOT VISION SYSTEM

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001493000066 ◽

1993 ◽

Vol 07 (01) ◽

pp. 89-107 ◽

Cited By ~ 6

Author(s):

J.R.G. PRETLOVE ◽

G.A. PARKER

Keyword(s):

Stereo Vision ◽

Degrees Of Freedom ◽

Manufacturing Industry ◽

Vision System ◽

Low Cost ◽

Processing System ◽

Robot Vision ◽

Path Following ◽

Complex Problem ◽

Low Weight

This paper presents the design and development of a real-time eye-in-hand stereo-vision system to aid robot guidance in a manufacturing environment. The stereo vision head comprises a novel camera arrangement with servo-vergence, focus, and aperture that continuously provides high-quality images to a dedicated image processing system and parallel processing array. The stereo head has four degrees of freedom but it relies on the robot end-effector for all remaining movement. This provides the robot with exploratory sensing abilities allowing it to undertake a wider variety of less constrained tasks. Unlike other stereo vision research heads, the overriding factor in the Surrey head has been a truly integrated engineering approach in an attempt to solve an extremely complex problem. The head is low cost, low weight, employs state-of-the-art motor technology, is highly controllable and occupies a small-sized envelope. Its intended applications include high-accuracy metrology, 3-D path following, object recognition and tracking, parts manipulation and component inspection for the manufacturing industry.

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2A1-N-098 Position control based on stereo vision system with convergence(Robot Vision 1,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives)

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ◽

10.1299/jsmermd.2005.154_3 ◽

2005 ◽

Vol 2005 (0) ◽

pp. 154

Author(s):

Nobutaka Tsujiuchi ◽

Takayuki Koizumi ◽

Yasuhisa Genda

Keyword(s):

Stereo Vision ◽

Position Control ◽

Vision System ◽

Robot Vision ◽

Daily Lives ◽

Stereo Vision System

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Modeling and Analysis of a Humanoid Robot Active Stereo Vision Platform

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.55-57.868 ◽

2011 ◽

Vol 55-57 ◽

pp. 868-871

Author(s):

Qin Jun Du ◽

Xue Yi Zhang ◽

Xing Guo Huang

Keyword(s):

Stereo Vision ◽

Visual Servoing ◽

Humanoid Robot ◽

Vision System ◽

Robot Vision ◽

Calibration Method ◽

Living Environment ◽

Position Information ◽

Modeling And Analysis ◽

Active Stereo

Humanoid robot is not only expected to walk stably, but also is required to perform manipulation tasks autonomously in our work and living environment. This paper discusses the visual perception and the object manipulation based on visual servoing of a humanoid robot, an active robot vision model is built, and then the 3D location principle, the calibration method and precision of this model are analyzed. This active robot vision system with two DOF enlarges its visual field and the stereo is the most simple camera configuration for 3D position information.

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