Planning the trajectory of an object in a confined space using stationary machine vision systems

被引:0
作者
Urunov, Salavat [1 ]
Voronin, Viacheslav [1 ]
Semenishchev, Evgenii [1 ]
机构
[1] Moscow State Tech Univ STANKIN, 1a Vadkovsky, Moscow 127055, Russia
来源
OPTICAL METROLOGY AND INSPECTION FOR INDUSTRIAL APPLICATIONS X | 2023年 / 12769卷
关键词
machine vision; edge detection; preprocessing; multicriteria method; planning trajectory;
D O I
10.1117/12.2691558
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The article proposes an approach to the formation of the trajectory of the spatial movement of a controlled object in a confined space using stationary vision systems. For its implementation, the following main steps are used in the work: 1. Preprocessing of data generated by the machine vision system. The task includes multicriteria image processing in order to minimize the noise component and determine the boundaries of objects. 2. An automated method for adaptive non-local separation of objects on borders, background and objects. 3. Execution of the task of adaptive nonlocal binarization. 4. Building a mask of stationary and current moving objects. 5. Formation of an equidistant displacement trajectory. 6. Checking the trajectory by moving in adjacent frames. 7. Prediction and remeasurement of the position of objects in the frame based on displacement vectors and correction of the object's movement trajectory. 7. Formation of a control team to move an object in a confined space using stationary vision systems. To test the effectiveness, studies were conducted on a set of test sequences. The studies were carried out on a group of cameras in the visible spectrum (1920x1080, RGB, 8 bits) covering the entire field of view. The adaptability of the application of the proposed approach in solving complex problems is showed.
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页数:6
相关论文
共 10 条
[1]  
Davim J. P., 2014, MODERN MECH ENG
[2]   Review on Human-Robot Interaction During Collaboration in a Shared Workspace [J].
Galin, Rinat ;
Meshcheryakov, Roman .
INTERACTIVE COLLABORATIVE ROBOTICS (ICR 2019), 2019, 11659 :63-74
[3]  
He CH, 2020, PROC CVPR IEEE, P11870, DOI 10.1109/CVPR42600.2020.01189
[4]  
Lynch K. M., 2017, Modern Robotics: Mechanics, Planning, and Control, DOI [10.1017/9781316661239, DOI 10.1109/MCS.2019.2937265]
[5]  
Olszewski M., 2020, Pomiary Autom. Robot, V24, P5, DOI [10.14313/PAR235/5, DOI 10.14313/PAR235/5]
[6]   Algorithm combination of deblurring and denoising on video frames using the method search of local features on image [J].
Semenishchev, Evgeny .
XIII INTERNATIONAL SCIENTIFIC-TECHNICAL CONFERENCE DYNAMIC OF TECHNICAL SYSTEMS (DTS-2017), 2017, 132
[7]   Image denoising using a combined criterion [J].
Semenishchev, Evgeny ;
Marchuk, Vladimir ;
Shrafel, Igor ;
Dubovskov, Vadim ;
Onoyko, Tatyana ;
Maslennikov, Stansilav .
MOBILE MULTIMEDIA/IMAGE PROCESSING, SECURITY, AND APPLICATIONS 2016, 2016, 9869
[8]  
Semenishchev S. E., 2017, Electronic Imaging, V6, P90
[9]   Research on large-scale additive manufacturing based on multi-robot collaboration technology [J].
Shen Hongyao ;
Pan Lingnan ;
Qian Jun .
ADDITIVE MANUFACTURING, 2019, 30
[10]   Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries [J].
Wang, En-Ze ;
Lee, Chien-Chiang ;
Li, Yaya .
ENERGY ECONOMICS, 2022, 105