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Select Papers from the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 2885

Special Issue Editors

Prof. Dr. Tao He

E-Mail Website
Guest Editor
Shanghai University of Engineering Science, 333 Long Teng Road, Shanghai 201620, China
Interests: light and high strength material preparation; special robot design; complex equipment digital design
Prof. Dr. Lubin Hang

E-Mail Website
Guest Editor
Shanghai University of Engineering Science, 333 Long Teng Road, Shanghai 201620, China
Interests: robot mechanism; knot theory; mathematical mechanization; master-slave force tactile device; laser tracking robot calibration
Prof. Dr. Yanfeng Gao

E-Mail
Guest Editor
Shanghai University of Engineering Science, 333 Long Teng Road, Shanghai 201620, China
Interests: welding robot; precision machining technology

Special Issue Information

Dear Colleagues,

Robot technology is a kind of advanced technology which integrates computers, cybernetics, mechanisms, information and sensing technology, artificial intelligence, bionics, and other disciplines. Robots are mainly divided into industrial robots and special robots, which have important uses in industry, medicine, agriculture, the service industry, the construction industry, and even military fields.

The Special Issue will select excellent papers about sensor application from the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI 2020). The excellent papers will be sensor studies on topics related to robot control technology, intelligent perception systems, robot perception and data fusion, robot operating system, unmanned system control technology, intelligent control system, intelligent manufacturing technology, pilotless automobile.

Prof. Dr. Tao He
Prof. Dr. Lubin Hang
Prof. Dr. Yanfeng Gao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensors with robotics
  • intelligent perception systems
  • unmanned system control technology
  • intelligent control systems
  • sensors in intelligent manufacturing
  • sensors in automatic control

Published Papers (1 paper)

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Research

18 pages, 6191 KiB  
Article
Intelligent Perception System of Robot Visual Servo for Complex Industrial Environment
by Yongchao Luo, Shipeng Li and Di Li
Sensors 2020, 20(24), 7121; https://doi.org/10.3390/s20247121 - 11 Dec 2020
Cited by 9 | Viewed by 2415
Abstract
Robot control based on visual information perception is a hot topic in the industrial robot domain and makes robots capable of doing more things in a complex environment. However, complex visual background in an industrial environment brings great difficulties in recognizing the target [...] Read more.
Robot control based on visual information perception is a hot topic in the industrial robot domain and makes robots capable of doing more things in a complex environment. However, complex visual background in an industrial environment brings great difficulties in recognizing the target image, especially when a target is small or far from the sensor. Therefore, target recognition is the first problem that should be addressed in a visual servo system. This paper considers common complex constraints in industrial environments and proposes a You Only Look Once Version 2 Region of Interest (YOLO-v2-ROI) neural network image processing algorithm based on machine learning. The proposed algorithm combines the advantages of YOLO (You Only Look Once) rapid detection with effective identification of ROI (Region of Interest) pooling structure, which can quickly locate and identify different objects in different fields of view. This method can also lead the robot vision system to recognize and classify a target object automatically, improve robot vision system efficiency, avoid blind movement, and reduce the calculation load. The proposed algorithm is verified by experiments. The experimental result shows that the learning algorithm constructed in this paper has real-time image-detection speed and demonstrates strong adaptability and recognition ability when processing images with complex backgrounds, such as different backgrounds, lighting, or perspectives. In addition, this algorithm can also effectively identify and locate visual targets, which improves the environmental adaptability of a visual servo system Full article
(This article belongs to the Special Issue Select Papers from the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence)
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