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Special Issue "Advanced Sensors for Intelligent Control Systems"

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

Deadline for manuscript submissions: 31 October 2022 | Viewed by 1883

Special Issue Editors

Prof. Dr. Han-Pang Huang
E-Mail Website
Guest Editor
Mechanical Engineering Department, National Taiwan University, Taipei 10617, Taiwan
Interests: intelligent robotics; prosthetics; mechatronics systems; sensor fusion
Prof. Dr. Chun-Yeon Lin
E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Taiwan University, Taipei 10617, Taiwan
Interests: electromagnetic sensor; electrical impedance sensing system; mechatronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors are essential components for acquiring information for intelligent systems to improve control performance by estimating physical properties. The sensing information obtained from different physical systems has a broad spectrum of applications, such as torque sensing for joint feedback control in industrial automation or physical interaction with a human, force sensing to improve the precision of machining, eddy current sensing for non-destructive detection in the manufacturing process, electrical impedance sensing for abnormal object detection in diagnosis, magnetic localization in medical applications or indoor positions, navigation of autonomous vehicles, and visual feedback systems. The sensor design and development for control systems involve modeling, simulation of physical fields, and hardware implementation. This Special Issue covers the topics of various sensors utilized for control systems or mechatronics systems. The scope of the Special Issue includes but is not limited to:

  • Torque sensing in robotics systems
  • Force sensing in manufacturing applications
  • Eddy current sensor for nondestructive detection
  • Electrical impedance sensing for abnormal objection detection
  • Magnetic localization in medical applications or indoor positions
  • Navigation of autonomous vehicles
  • Visual feedback systems
  • Sensor design and modeling
  • Integration of sensors in control systems
  • Intelligent sensing systems

Prof. Dr. Han-Pang Huang
Prof. Dr. Chun-Yeon Lin
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 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.

Published Papers (4 papers)

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Research

Article
Effective Free-Driving Region Detection for Mobile Robots by Uncertainty Estimation Using RGB-D Data
Sensors 2022, 22(13), 4751; https://doi.org/10.3390/s22134751 - 23 Jun 2022
Viewed by 239
Abstract
Accurate segmentation of drivable areas and road obstacles is critical for autonomous mobile robots to navigate safely in indoor and outdoor environments. With the fast advancement of deep learning, mobile robots may now perform autonomous navigation based on what they learned in the [...] Read more.
Accurate segmentation of drivable areas and road obstacles is critical for autonomous mobile robots to navigate safely in indoor and outdoor environments. With the fast advancement of deep learning, mobile robots may now perform autonomous navigation based on what they learned in the learning phase. On the other hand, existing techniques often have low performance when confronted with complex situations since unfamiliar objects are not included in the training dataset. Additionally, the use of a large amount of labeled data is generally essential for training deep neural networks to achieve good performance, which is time-consuming and labor-intensive. Thus, this paper presents a solution to these issues by proposing a self-supervised learning method for the drivable areas and road anomaly segmentation. First, we propose the Automatic Generating Segmentation Label (AGSL) framework, which is an efficient system automatically generating segmentation labels for drivable areas and road anomalies by finding dissimilarities between the input and resynthesized image and localizing obstacles in the disparity map. Then, we train RGB-D datasets with a semantic segmentation network using self-generated ground truth labels derived from our method (AGSL labels) to get the pre-trained model. The results showed that our AGSL achieved high performance in labeling evaluation, and the pre-trained model also obtains certain confidence in real-time segmentation application on mobile robots. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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Article
Contact Compliance Based Visual Feedback for Tool Alignment in Robot Assisted Bone Drilling
Sensors 2022, 22(9), 3205; https://doi.org/10.3390/s22093205 - 21 Apr 2022
Cited by 1 | Viewed by 407
Abstract
In recent decades, robot-assisted surgery has been proven superior at providing more accurate outcomes than the conventional one, particularly in minimally invasive procedures. However, there are still limitations to these kinds of surgical robots. Accurate bone drilling on the steep and hard surface [...] Read more.
In recent decades, robot-assisted surgery has been proven superior at providing more accurate outcomes than the conventional one, particularly in minimally invasive procedures. However, there are still limitations to these kinds of surgical robots. Accurate bone drilling on the steep and hard surface of cortical bone is still challenging. The issues of slipping away from the target entry point on the bone surface and subsequently deviating from the desired path are still not completely solved. Therefore, in this paper, a force control is proposed to accompany the resolved motion rate controller in a handheld orthopedic robot system. The force control makes it possible to adjust the contact compliance of the drill to the bone surface. With the proper contact compliance, the drill can be prevented from deflecting in contact with the bone surface, and will eventually be directed to the target entry point. The experiments on test jig and vertebra phantom also show that the robot under the proposed contact compliance visual feedback control structure could produce better usability positioning accuracy under various contact disturbances than its counterpart. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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Article
Magnetic Reference Mark in a Linear Positioning System Generated by a Single Wiegand Pulse
Sensors 2022, 22(9), 3185; https://doi.org/10.3390/s22093185 - 21 Apr 2022
Viewed by 352
Abstract
A Wiegand sensor is composed of a strip of Wiegand wire and a pick-up coil. The research presented in this paper examines and characterizes the fast magnetization reversal in a Wiegand wire, which leads to changes in magnetic flux density in its pick-up [...] Read more.
A Wiegand sensor is composed of a strip of Wiegand wire and a pick-up coil. The research presented in this paper examines and characterizes the fast magnetization reversal in a Wiegand wire, which leads to changes in magnetic flux density in its pick-up coil to produce the so-called Wiegand pulse to be used as a reference mark in a linear positioning system. It was observed in this research that the magnitude and duration of the pulse voltage were independent of driving frequency, indicating that Wiegand effect sensors could be ideal for use as zero-speed transducers. The repeatability of the Wiegand pulse was found to vary with different magnetic flux intensities of external magnetic field, as well as the angle between the magnetic induction line and the Wiegand wire. Through calibrated experimental and numerical parametric studies, the mechanism for producing repeatable Wiegand pulses to be used as a reference mark for precision liner positioning systems was revealed, which represents the novelty of this research. On the basis of this mechanism, the optimal design combination of the Wiegand sensor’s position with respect to the magnetization source can be obtained. Utilizing commercially available Wiegand sensors, it was demonstrated in this research that with a Wiegand pulse serving as a magnetic reference mark, positioning repeatability of 0.3 um could be achieved, which is on the same order as optical scales. The work presented in this research has engineering implications as well as offering scientific insights into magnetization mechanisms for generating enough magnetic remanence to produce a Barkhausen jump, resulting in repeatable Wiegand for use as a reference mark in a linear positioning system. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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Article
Detection of Surface and Subsurface Flaws with Miniature GMR-Based Gradiometer
Sensors 2022, 22(8), 3097; https://doi.org/10.3390/s22083097 - 18 Apr 2022
Viewed by 494
Abstract
The eddy-current (EC) testing method is frequently utilized in the nondestructive inspection of conductive materials. To detect the minor and complex-shaped defects on the surface and in the underlying layers of a metallic sample, a miniature eddy-current probe with high sensitivity is preferred [...] Read more.
The eddy-current (EC) testing method is frequently utilized in the nondestructive inspection of conductive materials. To detect the minor and complex-shaped defects on the surface and in the underlying layers of a metallic sample, a miniature eddy-current probe with high sensitivity is preferred for enhancing the signal quality and spatial resolution of the obtained eddy-current images. In this work, we propose a novel design of a miniature eddy-current probe using a giant magnetoresistance (GMR) sensor fabricated on a silicon chip. The in-house-made GMR sensor comprises two cascaded spin-valve elements in parallel with an external variable resistor to form a Wheatstone bridge. The two elements on the chip are excited by the alternating magnetic field generated by a tiny coil aligned to the position that balances the background output of the bridge sensor. In this way, the two GMR elements behave effectively as an axial gradiometer with the bottom element sensitive to the surface and near-surface defects on a conductive specimen. The performance of the EC probe is verified by the numerical simulation and the corresponding experiments with machined defects on metallic samples. With this design, the geometric characteristics of the defects are clearly visualized with a spatial resolution of about 1 mm. The results demonstrate the feasibility and superiority of the proposed miniature GMR EC probe for characterizing the small and complex-shaped defects in multilayer conductive samples. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Dear Colleagues,

Sensors are essential components for acquiring information for intelligent systems to improve control performance by estimating physical properties. The sensing information obtained from different physical systems has a broad spectrum of applications, such as torque sensing for joint feedback control in industrial automation or physical interaction with a human, force sensing to improve the precision of machining, eddy current sensing for non-destructive detection in the manufacturing process, electrical impedance sensing for abnormal object detection in diagnosis, magnetic localization in medical applications or indoor positions, navigation of autonomous vehicles, and visual feedback systems. The sensor design and development for control systems involve modeling, simulation of physical fields, and hardware implementation. This Special Issue covers the topics of various sensors utilized for control systems or mechatronics systems. The scope of the Special Issue includes but is not limited to:

  • Torque sensing in robotics systems
  • Force sensing in manufacturing applications
  • Eddy current sensor for nondestructive detection
  • Electrical impedance sensing for abnormal objection detection
  • Magnetic localization in medical applications or indoor positions
  • Navigation of autonomous vehicles
  • Visual feedback systems
  • Sensor design and modeling
  • Integration of sensors in control systems
  • Intelligent sensing systems

Prof. Dr. Han-Pang Huang
Prof. Dr. Chun-Yeon Lin
Guest Editors

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