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Electronics
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Robot-Vision-Based Control Systems
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Robot-Vision-Based Control Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 15 February 2025 | Viewed by 1121

Special Issue Editors

Prof. Dr. Zainan Jiang

E-Mail Website
Guest Editor
State Key Laboratory of Robotics and System, School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
Interests: land–air cross-domain robots; robot teleoperation; motion planning; human–computer interactions
Prof. Dr. Ting Zhang

E-Mail Website
Guest Editor
Robotics and Microsystems Center, Soochow University, Suzhou 215000, China
Interests: multi-fingered hand for robots and prostheses; wearable robot; and human–robot interactions
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Xiaohua Xia

E-Mail Website
Guest Editor
School of Construction Machinery, Chang’an University, Xi’an 710064, China
Interests: machine vision; opto-mechatronics

Special Issue Information

Dear Colleagues,

Various robots are widely being utilized in many settings, such as factories, families, emergency rescue, etc. Robot vision is the prime channel to perceive the surrounding environment and identify the work object for the robot. Guided by visual perception technology, it realizes the perception and fusion of information from one-dimensional, two-dimensional to multi-dimensional, achieving fast and accurate environmental perception and object recognition, which enable the robots to locomote and manipulate safely and efficiently in unknown environments.

For this Special Issue, we are interested in receiving theoretical and practical articles on the latest technologies and applications of robot-vision-based control systems. The topics of interest include, but are not limited to, the following:

(1) Innovative robot vision sensors;

(2) Intelligent vision detection;

(3) Augmented, virtual and mixed reality (AR/VR/MR);

(4) Simultaneous localization and mapping (SLAM);

(5) Vision-based human–robot interactions;

(6) Visual servo control.

Prof. Dr. Zainan Jiang
Prof. Dr. Ting Zhang
Prof. Dr. Xiaohua Xia
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. Electronics 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 2400 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

  • vision sensor
  • vision inspection
  • SLAM
  • visual serving

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Published Papers (2 papers)

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Research

19 pages, 8713 KiB  
Article
Precise Orientation Estimation for Rotated Object Detection Based on a Unit Vector Coding Approach
by Chi-Yi Tsai and Wei-Chuan Lin
Electronics 2024, 13(22), 4402; https://doi.org/10.3390/electronics13224402 - 10 Nov 2024
Viewed by 579
Abstract
Existing rotated object detection methods usually use angular parameters to represent the object orientation. However, due to the symmetry and periodicity of these angular parameters, a well-known boundary discontinuity problem often results. More specifically, when the object orientation angle approaches the periodic boundary, [...] Read more.
Existing rotated object detection methods usually use angular parameters to represent the object orientation. However, due to the symmetry and periodicity of these angular parameters, a well-known boundary discontinuity problem often results. More specifically, when the object orientation angle approaches the periodic boundary, the predicted angle may change rapidly and adversely affect model training. To address this problem, this paper introduces a new method that can effectively solve the boundary discontinuity problem related to angle parameters in rotated object detection. Our approach involves a novel vector-based encoding and decoding technique for angular parameters, and a cosine distance loss function for angular accuracy evaluation. By utilizing the characteristics of unit vectors and cosine similarity functions, our method parameterizes the orientation angle as components of the unit vector during the encoding process and redefines the orientation angle prediction task as a vector prediction problem, effectively avoiding the boundary discontinuity problem. The proposed method achieved a mean average precision (mAP) of 87.48% and an average cosine similarity (CS) of 0.997 on the MVTec test set. It also achieved an mAP score of 90.54% on the HRSC2016 test set, which is better than several existing state-of-the-art methods and proves its accuracy and effectiveness. Full article
(This article belongs to the Special Issue Robot-Vision-Based Control Systems)
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21 pages, 14386 KiB  
Article
A High-Quality and Convenient Camera Calibration Method Using a Single Image
by Xufang Qin, Xiaohua Xia and Huatao Xiang
Electronics 2024, 13(22), 4361; https://doi.org/10.3390/electronics13224361 - 6 Nov 2024
Viewed by 366
Abstract
Existing camera calibration methods using a single image have exhibited some limitations. These limitations include relying on large datasets, using inconveniently prepared calibration objects instead of commonly used planar patterns such as checkerboards, and requiring further improvement in accuracy. To address these issues, [...] Read more.
Existing camera calibration methods using a single image have exhibited some limitations. These limitations include relying on large datasets, using inconveniently prepared calibration objects instead of commonly used planar patterns such as checkerboards, and requiring further improvement in accuracy. To address these issues, a high-quality and convenient camera calibration method is proposed, which only requires a single image of the commonly used planar checkerboard pattern. In the proposed method, a nonlinear objective function is derived by leveraging the linear distribution characteristics exhibited among corners. An algorithm based on enumeration theory is designed to minimize this function. It calibrates the first two radial distortion coefficients and principal points. The focal length and extrinsic parameters are linearly calibrated from the constraints provided by the linear projection model and the unit orthogonality of the rotation matrix. Additionally, a guideline is explored through theoretical analysis and numerical simulation to ensure calibration quality. The quality of the proposed method is evaluated by both simulated and real experiments, demonstrating its comparability with the well-known multi-image-based method and its superiority over advanced single-image-based methods. Full article
(This article belongs to the Special Issue Robot-Vision-Based Control Systems)
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