Research on Manipulator Positioning Based on Stereo Vision in Virtual Environment

Inherent uncertainties always exist in the positioning picking manipulators in complex environment, modeling and simulation of positioning. The manipulators were discussed based on binocular stereo vision in virtual environment (VE). Based on stereo vision, a method how virtual manipulators locate picking object by human-computer interaction (HCI) was proposed. The data input from vision were mapped to virtual picking manipulators so that it could enable the positioning and simulation with route and events-driven mechanism. The positioning experimental platform in VE consists of hardware of CCD stereo vision and simulation software. The visualized simulation system was exploited by EON SDK. The simulation of manipulator’s positioning was realized in VE by the platform. This method can be used for virtual robot to locate objects’ long-distance positioning in complex environment.

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Research on Ranging Method Based on Binocular Stereo Vision

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.945-949.2075 ◽

2014 ◽

Vol 945-949 ◽

pp. 2075-2081 ◽

Cited By ~ 2

Author(s):

Xue Zhi Lv ◽

Mei Ting Wang ◽

Yong Feng Qi ◽

Xue Mei Zhao ◽

Hao Dong

Keyword(s):

Camera Calibration ◽

Stereo Vision ◽

Experimental Platform ◽

Binocular Stereo Vision ◽

Parallel Arrangement ◽

Binocular Stereo ◽

Contour Boundary ◽

Measurement Object ◽

Stereo Calibration ◽

Left And Right

Binocular stereo vision ranging method taking contour boundary center of measurement object as matching features was investigated. And experimental platform for binocular stereo vision ranging system was built up. The stereo vision ranging system comprised four modules: camera calibration, stereo calibration, stereo rectification and features extraction. Firstly, the intrinsic parameters of single camera were obtained by camera calibration and relative pose of two cameras was obtained by stereo calibration. Then the left and right images were rectified into a frontal parallel arrangement by Bouguet’s method. The edge pixels of contours were detected by image processing. Then the disparity and the distance was calculated taking contour center as matching features. Finally, measurement error analysis was performed to verify the proposed method with good practicability.

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Study on behavior simulation for picking manipulator in virtual environment based on binocular stereo vision

2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing ◽

10.1109/asc-icsc.2008.4675320 ◽

2008 ◽

Author(s):

Hongjun Wang ◽

Xiangjun Zou ◽

Changyu Liu ◽

Jun Lu ◽

Tianhu Liu

Keyword(s):

Virtual Environment ◽

Stereo Vision ◽

Behavior Simulation ◽

Binocular Stereo Vision ◽

Binocular Stereo

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Combing Structured Light Measurement Technology with Binocular Stereo Vision

2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) ◽

10.1109/cyber.2017.8446499 ◽

2017 ◽

Author(s):

Qi Zhou ◽

YongMing Yang ◽

ZhenZhou Wang

Keyword(s):

Stereo Vision ◽

Structured Light ◽

Measurement Technology ◽

Binocular Stereo Vision ◽

Light Measurement ◽

Binocular Stereo

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Application of integrated binocular stereo vision measurement and wireless sensor system in athlete displacement test

Alexandria Engineering Journal ◽

10.1016/j.aej.2021.02.033 ◽

2021 ◽

Vol 60 (5) ◽

pp. 4325-4335

Author(s):

Haizhen Li ◽

Baojun Zhang

Keyword(s):

Stereo Vision ◽

Sensor System ◽

Wireless Sensor ◽

Vision Measurement ◽

Binocular Stereo Vision ◽

Binocular Stereo ◽

Stereo Vision Measurement

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High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10040234 ◽

2021 ◽

Vol 10 (4) ◽

pp. 234

Author(s):

Jing Ding ◽

Zhigang Yan ◽

Xuchen We

Keyword(s):

Stereo Vision ◽

Stereo Matching ◽

Three Dimensional ◽

Target Localization ◽

Parallel Structure ◽

Moving Target ◽

Target Area ◽

Moving Targets ◽

Binocular Stereo Vision ◽

Binocular Stereo

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

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