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Applied Robotics in Mechatronics and Automation

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

Deadline for manuscript submissions: 31 May 2025 | Viewed by 6849

Special Issue Editor

Prof. Dr. Yueh-Jaw (YJ) Lin

E-Mail Website
Guest Editor
Mechanical Engineering Department, College of Engineering and Engineering Technology, Northern Illinois University, DeKalb, IL, USA
Interests: mechatronics engineering; applied robotics in design and automation; aircraft deicing and health monitoring; renewable energy and energy harvesting; global engineering education and research

Special Issue Information

Dear Colleagues,

Mechatronics and automation technologies significantly rely on the use of sensors, which play a pivotal role in collecting data, enabling precise control, ensuring the safety and efficiency of robotic systems, as well as enhancing the perception, navigation, and interaction capabilities of robots and mechatronic systems.

This Special Issue of Sensors titled ‘Applied Robotics in Mechatronics and Automation’ invites submissions of research articles that focus on the intersection of robotics, mechatronics and automation, highlight the recent advancements in their theoretical as well as practical applications, thereby underscoring the importance of applied robotics and automation technologies in the digital future.

Potential topics include, but are not limited to, robotics, mechatronics, automation, artificial intelligence, sensing technologies, human–machine interaction, industrial applications, autonomous systems, control systems, and machine learning.

Prof. Dr. Yueh-Jaw (YJ) Lin
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. 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.

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Published Papers (6 papers)

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Research

21 pages, 9003 KiB  
Article
An Investigation on the Ball Screw-Based Variable Displacement Mechanism for Axial Piston Pumps with Feedforward Differential Input Control
by Guangcheng Zhang, Bokai Wang and Yueh-Jaw Lin
Sensors 2025, 25(4), 994; https://doi.org/10.3390/s25040994 - 7 Feb 2025
Viewed by 602
Abstract
This paper proposes a variable mechanism structure based on a ball screw design for precise displacement control in axial piston pumps, with the objective of improving actuator position and velocity control within the displacement-controlled (DC) systems. Traditional valve-controlled cylinder variable mechanisms (VCCVM) often [...] Read more.
This paper proposes a variable mechanism structure based on a ball screw design for precise displacement control in axial piston pumps, with the objective of improving actuator position and velocity control within the displacement-controlled (DC) systems. Traditional valve-controlled cylinder variable mechanisms (VCCVM) often suffer from limited control precision over the swash plate due to numerous uncertain parameters within the hydraulic system. To address this issue, a ball screw is utilized to replace the original valve-controlled cylinder for swash plate control, enhancing accuracy and responsiveness. In addition, an in-depth analysis of the Ball Screw Variable Mechanism (BSVM) is conducted, leading to the development of a coupled mechanical–hydraulic dynamic model. Based on this model, a controller is designed to improve system performance. Finally, the effectiveness and high performance of the proposed new structure and control strategy were validated through comparative experiments and simulations. The experimental results confirm the advantages of the proposed design, demonstrating satisfactory improvements in control precision. Full article
(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)
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18 pages, 1590 KiB  
Article
Design and Evaluation of a Low-Cost Mount for Attaching a Laser Tracker’s SMR to a Robot Flange
by Florian Stöckl, Silvan Müller, Marcus Strand and Markus Gardill
Sensors 2025, 25(1), 184; https://doi.org/10.3390/s25010184 - 31 Dec 2024
Viewed by 679
Abstract
Robot calibration and modelling measurements are commonly performed using a laser tracker. To capture three-dimensional positions, a SMR is attached to the robot. While some researchers employ adhesive bonds for this purpose, such methods often result in inaccurate, unstable and non-repeatable SMR positioning, [...] Read more.
Robot calibration and modelling measurements are commonly performed using a laser tracker. To capture three-dimensional positions, a SMR is attached to the robot. While some researchers employ adhesive bonds for this purpose, such methods often result in inaccurate, unstable and non-repeatable SMR positioning, adversely affecting measurement precision and the traceability of research outcomes. To address these challenges, we investigated alternative methods for attaching an SMR to a robot’s flange to achieve both accuracy and repeatability. Additionally, we analysed measurement errors introduced when using a tool to attach the SMR to the flange. As a solution, we developed a 3D-printed mount designed for attachment to the flange. The mount’s accuracy was evaluated by assessing its eccentricity and the repeatability of the SMR placement. Experimental results demonstrated that the mount achieved an eccentricity radius of 0.35 mm and repeatability inaccuracies of X=0.075mm, Y=0.328mm, and Z=0.485mm. These values indicate that the mount provides sufficient accuracy to support calibration processes, ensures research traceability, and serves as a viable replacement for adhesive bonds. Full article
(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)
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15 pages, 2177 KiB  
Article
DDNet: Depth Dominant Network for Semantic Segmentation of RGB-D Images
by Peizhi Rong
Sensors 2024, 24(21), 6914; https://doi.org/10.3390/s24216914 - 28 Oct 2024
Viewed by 1217
Abstract
Convolutional neural networks (CNNs) have been widely applied to parse indoor scenes and segment objects represented by color images. Nonetheless, the lack of geometric and context information is a problem for most RGB-based methods, with which depth features are only used as an [...] Read more.
Convolutional neural networks (CNNs) have been widely applied to parse indoor scenes and segment objects represented by color images. Nonetheless, the lack of geometric and context information is a problem for most RGB-based methods, with which depth features are only used as an auxiliary module in RGB-D semantic segmentation. In this study, a novel depth dominant network (DDNet) is proposed to fully utilize the rich context information in the depth map. The critical insight is that obvious geometric information from the depth image is more conducive to segmentation than RGB data. Compared with other methods, DDNet is a depth-based network with two branches of CNNs to extract color and depth features. As the core of the encoder network, the depth branch is given a larger fusion weight to extract geometric information, while semantic information and complementary geometric information are provided by the color branch for the depth feature maps. The effectiveness of our proposed depth-based architecture has been demonstrated by comprehensive experimental evaluations and ablation studies on challenging RGB-D semantic segmentation benchmarks, including NYUv2 and a subset of ScanNetv2. Full article
(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)
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16 pages, 7405 KiB  
Article
Multi-AUV Kinematic Task Assignment Based on Self-Organizing Map Neural Network and Dubins Path Generator
by Xin Li, Wenyang Gan, Wen Pang and Daqi Zhu
Sensors 2024, 24(19), 6345; https://doi.org/10.3390/s24196345 - 30 Sep 2024
Viewed by 998
Abstract
To deal with the task assignment problem of multi-AUV systems under kinematic constraints, which means steering capability constraints for underactuated AUVs or other vehicles likely, an improved task assignment algorithm is proposed combining the Dubins Path algorithm with improved SOM neural network algorithm. [...] Read more.
To deal with the task assignment problem of multi-AUV systems under kinematic constraints, which means steering capability constraints for underactuated AUVs or other vehicles likely, an improved task assignment algorithm is proposed combining the Dubins Path algorithm with improved SOM neural network algorithm. At first, the aimed tasks are assigned to the AUVs by the improved SOM neural network method based on workload balance and neighborhood function. When there exists kinematic constraints or obstacles which may cause failure of trajectory planning, task re-assignment will be implemented by changing the weights of SOM neurals, until the AUVs can have paths to reach all the targets. Then, the Dubins paths are generated in several limited cases. The AUV’s yaw angle is limited, which results in new assignments to the targets. Computation flow is designed so that the algorithm in MATLAB and Python can realize the path planning to multiple targets. Finally, simulation results prove that the proposed algorithm can effectively accomplish the task assignment task for a multi-AUV system. Full article
(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)
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18 pages, 3329 KiB  
Article
Robot Calibration Sampling Data Optimization Method Based on Improved Robot Observability Metrics and Binary Simulated Annealing Algorithm
by Huakun Jia, Hanbo Zeng, Jiyan Zhang, Xiangyang Wang, Yang Lu and Liandong Yu
Sensors 2024, 24(19), 6171; https://doi.org/10.3390/s24196171 - 24 Sep 2024
Viewed by 1080
Abstract
As the societal demand for precision in industrial robot operations increases, calibration can enhance the end-effector positioning accuracy of robots. Sampling data optimization plays an important role in improving the calibration effect. In this study, a robot calibration sampling point optimization method based [...] Read more.
As the societal demand for precision in industrial robot operations increases, calibration can enhance the end-effector positioning accuracy of robots. Sampling data optimization plays an important role in improving the calibration effect. In this study, a robot calibration sampling point optimization method based on improved robot observability metrics and a Binary Simulated Annealing Algorithm is proposed. Initially, a robot kinematic model based on the Product of Exponentials (POE) model and a generalized error model is established. By utilizing the least squares method, the ideal pose transformation relationship between the robot’s base coordinate system and the laser tracker measurement coordinate system is derived, resulting in an error calibration model based on spatial single points. An improved robot observability metric combined with the Binary Simulated Annealing Algorithm (BSAA) is introduced to optimize the selection of calibration sampling data. Finally, the robot’s parameter errors are obtained using a nonlinear least squares method. Experimental results demonstrate that the average end-effector positioning error of the robot after calibration can be reduced from 0.356 mm to 0.254 mm using this method. Full article
(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)
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25 pages, 5922 KiB  
Article
GNSS-Based Narrow-Angle UV Camera Targeting: Case Study of a Low-Cost MAD Robot
by Ntmitrii Gyrichidi, Alexey M. Romanov, Oleg V. Trofimov, Stanislav A. Eroshenko, Pavel V. Matrenin and Alexandra I. Khalyasmaa
Sensors 2024, 24(11), 3494; https://doi.org/10.3390/s24113494 - 28 May 2024
Cited by 3 | Viewed by 1408
Abstract
One of the key challenges in Multi-Spectral Automatic Diagnostic (MAD) robot design is the precise targeting of narrow-angle cameras on a specific part of the equipment. The paper shows that a low-cost MAD robot, whose navigation system is based on open-source ArduRover firmware [...] Read more.
One of the key challenges in Multi-Spectral Automatic Diagnostic (MAD) robot design is the precise targeting of narrow-angle cameras on a specific part of the equipment. The paper shows that a low-cost MAD robot, whose navigation system is based on open-source ArduRover firmware and a pair of low-cost Ublox F9P GNSS receivers, can inspect the 8 × 4 degree ultraviolet camera bounding the targeting error within 0.5 degrees. To achieve this result, we propose a new targeting procedure that can be implemented without any modifications in ArduRover firmware and outperforms more expensive solutions based on LiDAR SLAM and UWB. This paper will be interesting to the developers of robotic systems for power equipment inspection because it proposes a simple and effective solution for MAD robots’ camera targeting and provides the first quantitative analysis of the GNSS reception conditions during power equipment inspection. This analysis is based on the experimental results collected during the inspection of the overhead power transmission lines and equipment inspections on the open switchgear of different power plants. Moreover, it includes not only satellite, dilution of precision, and positioning/heading estimation accuracy but also the direct measurements of angular errors that could be achieved on operating power plants using GNSS-only camera targeting. Full article
(This article belongs to the Special Issue Applied Robotics in Mechatronics and Automation)
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