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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: closed (1 May 2023) | Viewed by 18262

Special Issue Editors


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Guest Editor
Mechanical Engineering Department, National Taiwan University, Taipei 10617, Taiwan
Interests: intelligent robotics; prosthetics; mechatronics systems; sensor fusion

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

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Published Papers (9 papers)

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Research

24 pages, 7132 KiB  
Article
The Five-DOF Explosion-Removal Manipulator Based on Position and Velocity Feedforward Compensation Control
by Jianwei Zhao and Jiaxin Zhou
Sensors 2023, 23(9), 4276; https://doi.org/10.3390/s23094276 - 25 Apr 2023
Viewed by 1196
Abstract
The main problem with a robotic system arm is its sensitivity to time delays in the control process. Due to this problem, it is necessary to further optimize the control process of the system. One solution is to deal with the control accuracy [...] Read more.
The main problem with a robotic system arm is its sensitivity to time delays in the control process. Due to this problem, it is necessary to further optimize the control process of the system. One solution is to deal with the control accuracy and response speed issues of robotic arm joints, to improve the system’s response performance and enhance the system’s anti-interference ability. This paper proposes a speed feedforward and position control scheme for robotic arm joint control. The conclusion section shows that compared to traditional five-degree-of-freedom robotic arm systems, the addressed robotic arm control system has a lower tracking delay and better dynamic response performance. It can improve the system’s response performance while also enhancing its anti-interference ability. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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19 pages, 6283 KiB  
Article
Development of a Visual Perception System on a Dual-Arm Mobile Robot for Human-Robot Interaction
by Wei-Ting Weng, Han-Pang Huang, Yu-Lin Zhao and Chun-Yeon Lin
Sensors 2022, 22(23), 9545; https://doi.org/10.3390/s22239545 - 6 Dec 2022
Cited by 4 | Viewed by 2132
Abstract
This paper presents the development of a visual-perception system on a dual-arm mobile robot for human-robot interaction. This visual system integrates three subsystems. Hand gesture recognition is utilized to trigger human-robot interaction. Engagement and intention of the participants are detected and quantified through [...] Read more.
This paper presents the development of a visual-perception system on a dual-arm mobile robot for human-robot interaction. This visual system integrates three subsystems. Hand gesture recognition is utilized to trigger human-robot interaction. Engagement and intention of the participants are detected and quantified through a cognitive system. Visual servoing uses YOLO to identify the object to be tracked and hybrid, model-based tracking to follow the object’s geometry. The proposed visual-perception system is implemented in the developed dual-arm mobile robot, and experiments are conducted to validate the proposed method’s effects on human-robot interaction applications. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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17 pages, 5011 KiB  
Article
A Hybrid State/Disturbance Observer-Based Feedback Control of Robot with Multiple Constraints
by Du Xu, Tete Hu, Ying Ma and Xin Shu
Sensors 2022, 22(23), 9112; https://doi.org/10.3390/s22239112 - 24 Nov 2022
Viewed by 1123
Abstract
Controlling the manipulator is a big challenge due to its hysteresis, deadzone, saturation, and the disturbances of actuators. This study proposes a hybrid state/disturbance observer-based multiple-constraint control mechanism to address this difficulty. It first proposes a hybrid state/disturbance observer to simultaneously estimate the [...] Read more.
Controlling the manipulator is a big challenge due to its hysteresis, deadzone, saturation, and the disturbances of actuators. This study proposes a hybrid state/disturbance observer-based multiple-constraint control mechanism to address this difficulty. It first proposes a hybrid state/disturbance observer to simultaneously estimate the unmeasurable states and external disturbances. Based on this, a barrier Lyapunov function is proposed and implemented to handle output saturation constraints, and a back-stepping control method is developed to provide sufficient control performance under multiple constraints. Furthermore, the stability of the proposed controller is analyzed and proved. Finally, simulations and experiments are carried out on a 2-DOF and 6-DOF robot, respectively. The results show that the proposed control method can effectively achieve the desired control performance. Compared with several commonly used control methods and intelligent control methods, the proposed method shows superiority. Experiments on a 6-DOF robot verify that the proposed method has good tracking performance for all joints and does not violate constraints. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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15 pages, 5990 KiB  
Article
Two-Dimensional Position Tracking Using Gradient Magnetic Fields
by Xuan Thang Trinh, Jen-Tzong Jeng, Huu-Thang Nguyen, Van Su Luong and Chih-Cheng Lu
Sensors 2022, 22(14), 5459; https://doi.org/10.3390/s22145459 - 21 Jul 2022
Cited by 2 | Viewed by 2095
Abstract
In this work, a two-dimensional (2D) position-detection device using a single axis magnetic sensor combined with orthogonal gradient coils was designed and fabricated. The sensors used were an induction coil and a GMR spin-valve sensor GF807 from Sensitec Inc. The field profiles generated [...] Read more.
In this work, a two-dimensional (2D) position-detection device using a single axis magnetic sensor combined with orthogonal gradient coils was designed and fabricated. The sensors used were an induction coil and a GMR spin-valve sensor GF807 from Sensitec Inc. The field profiles generated by the two orthogonal gradient coils were analyzed numerically to achieve the maximum linear range, which corresponded to the detection area of the tracking system. The two coils were driven by 1-kHz sine wave currents with a 90° phase difference to generate the fields with uniform gradients along the x- and y-axis in the plane of the tracking stage. The gradient fields were detected by a single-axis sensor incorporated with a digital dual-phase lock-in detector to retrieve the position information. A linearity correction algorithm was used to improve the location accuracy and to extend the linear range for position sensing. The mean positioning error was found to be 0.417 mm, corresponding to the relative error of 0.21% in the working range of 200 mm × 200 mm, indicating that the proposed tracking system is promising for applications requiring accurate control of the two-dimensional position. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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21 pages, 2756 KiB  
Article
An Image-Based Data-Driven Model for Texture Inspection of Ground Workpieces
by Yu-Hsun Wang, Jing-Yu Lai, Yuan-Chieh Lo, Chih-Hsuan Shih and Pei-Chun Lin
Sensors 2022, 22(14), 5192; https://doi.org/10.3390/s22145192 - 11 Jul 2022
Cited by 2 | Viewed by 1578
Abstract
Nowadays, the grinding process is mostly automatic, yet post-grinding quality inspection is mostly carried out manually. Although the conventional inspection technique may have cumbersome setup and tuning processes, the data-driven model, with its vision-based dataset, provides an opportunity to automate the inspection process. [...] Read more.
Nowadays, the grinding process is mostly automatic, yet post-grinding quality inspection is mostly carried out manually. Although the conventional inspection technique may have cumbersome setup and tuning processes, the data-driven model, with its vision-based dataset, provides an opportunity to automate the inspection process. In this study, a convolutional neural network technique with transfer learning is proposed for three kinds of inspections based on 750–1000 surface raw images of the ground workpieces in each task: classifying the grit number of the abrasive belt that grinds the workpiece, estimating the surface roughness of the ground workpiece, and classifying the degree of wear of the abrasive belts. The results show that a deep convolutional neural network can recognize the texture on the abrasive surface images and that the classification model can achieve an accuracy of 0.9 or higher. In addition, the external coaxial white light was the most suitable light source among the three tested light sources: the external coaxial white light, the high-angle ring light, and the external coaxial red light. Finally, the model that classifies the degree of wear of the abrasive belts can also be utilized as the abrasive belt life estimator. Full article
(This article belongs to the Special Issue Advanced Sensors for Intelligent Control Systems)
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14 pages, 4254 KiB  
Article
Effective Free-Driving Region Detection for Mobile Robots by Uncertainty Estimation Using RGB-D Data
by Toan-Khoa Nguyen, Phuc Thanh-Thien Nguyen, Dai-Dong Nguyen and Chung-Hsien Kuo
Sensors 2022, 22(13), 4751; https://doi.org/10.3390/s22134751 - 23 Jun 2022
Cited by 2 | Viewed by 2047
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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11 pages, 9767 KiB  
Article
Contact Compliance Based Visual Feedback for Tool Alignment in Robot Assisted Bone Drilling
by Ping-Lang Yen and Yu-Jui Chen
Sensors 2022, 22(9), 3205; https://doi.org/10.3390/s22093205 - 21 Apr 2022
Cited by 4 | Viewed by 2334
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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13 pages, 3999 KiB  
Article
Magnetic Reference Mark in a Linear Positioning System Generated by a Single Wiegand Pulse
by Hung-Lin Lien and Jen-Yuan Chang
Sensors 2022, 22(9), 3185; https://doi.org/10.3390/s22093185 - 21 Apr 2022
Cited by 6 | Viewed by 1914
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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22 pages, 9642 KiB  
Article
Detection of Surface and Subsurface Flaws with Miniature GMR-Based Gradiometer
by Huu-Thang Nguyen, Jen-Tzong Jeng, Van-Dong Doan, Chinh-Hieu Dinh, Xuan Thang Trinh and Duy-Vinh Dao
Sensors 2022, 22(8), 3097; https://doi.org/10.3390/s22083097 - 18 Apr 2022
Viewed by 2298
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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