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Electronics
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Advanced Technologies in Robotics and Smart Manufacturing
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Advanced Technologies in Robotics and Smart Manufacturing

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

Deadline for manuscript submissions: 15 November 2024 | Viewed by 948

Special Issue Editor

Dr. Sangram Redkar

E-Mail Website
Guest Editor
School of Manufacturing Systems and Networks, Ira Fulton School of Engineering, Arizona State University, Mesa, AZ 85212, USA
Interests: physiological sensing; dynamics; control; robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will focus on recent technological advances in robotics, autonomous systems, and smart manufacturing. It will focus on various topics in robotics, including but not limited to digital twins, swarm robotics, robot teaming, robots in manufacturing, industrial automation, human robot teaming, wearable robots, medical robotics, machine learning, smart and digital manufacturing, drones, etc.

Original articles related to drones, human–robot interactions, Generative AI and its applications in robotics and manufacturing, smart and distributed manufacturing, recent trends in automation, applications of digital twins, Digital Shadows for robotics and manufacturing, human digital twin and its interface with robotic digital twin, Cognitive Digital Twin, and ultra-lean decentralized manufacturing are welcome.

Dr. Sangram Redkar
Guest Editor

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

  • digital twin
  • medical robots
  • smart and distributed manufacturing

Published Papers (1 paper)

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Research

17 pages, 6407 KiB  
Article
Research on Forging Dimension Online Measuring System Based on Vibration Point Cloud Compensation
by Shaoshun Bian, Bin Zhang, Xiuhong Han, Mingxin Yuan, Jiawei Xu and Debin Shan
Electronics 2024, 13(13), 2494; https://doi.org/10.3390/electronics13132494 - 26 Jun 2024
Viewed by 803
Abstract
Mechanical vibration in the high-temperature forging production line often causes large forging thermal dimensional measurement error in the detection task, so a vibration point cloud compensation method based on an acceleration sensor is proposed in this study. First, the vibration signal is obtained [...] Read more.
Mechanical vibration in the high-temperature forging production line often causes large forging thermal dimensional measurement error in the detection task, so a vibration point cloud compensation method based on an acceleration sensor is proposed in this study. First, the vibration signal is obtained through the built-in acceleration sensor in the laser camera. After the acceleration of the camera vibration is detected, the displacement of the camera in three directions is solved by secondary integration. Subsequently, the coordinate value of the corresponding point is obtained by the rotation matrix transformation so as to compensate and correct the point cloud deviation caused by the camera vibration. Finally, the forging point cloud is matched using the surface matching algorithm in Halcon. An automatic forging production line for wheel hubs has been built, and the key dimensions of high-temperature forging products have been measured online using the developed method. After the forging point cloud is compensated, the average measurement error of dimensions is reduced from ±0.9 mm to ±0.1 mm, and the standard deviation is reduced from 0.52 mm to 0.056 mm. Using the vibration point cloud compensation method based on the acceleration sensor, as well as using silica aerogel insulation, vibration structural parts, heat insulation and constant temperature, a blue-violet 3D laser camera, and other measures, the dimensional detection accuracy of high-temperature forgings in the forging production line can be improved, and the instability of dimensional detection can be reduced. Full article
(This article belongs to the Special Issue Advanced Technologies in Robotics and Smart Manufacturing)
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