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Assembly Complexity Index (ACI) for Modular Robotic Systems: Validation and Conceptual Framework for AR/VR-Assisted Assembly
A Review of Artificial Intelligence-Driven Active Vibration and Noise Control

Journal Description

Machines

Machines is an international, peer-reviewed, open access journal on machinery and engineering published monthly online by MDPI. The IFToMM is affiliated with Machines and its members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, and other databases.
Journal Rank: JCR - Q2 (Engineering, Mechanical) / CiteScore - Q1 (Control and Optimization)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.4 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Journal Cluster of Mechanical Manufacturing and Automation Control: Aerospace, Automation, Drones, Journal of Manufacturing and Materials Processing, Machines, Robotics and Technologies.

Impact Factor: 2.5 (2024); 5-Year Impact Factor: 2.6 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2075-1702

Latest Articles

18 pages, 9923 KB

Open AccessArticle

Vibration Characteristics and Fatigue Performance of Bogie Frame with Inner Axle Box for High-Speed Trains

by Tao Guo, Bingzhi Chen, Yuedong Wang, Guojie Cai, Maorui Hou and Qi Dong

Machines 2025, 13(11), 1056; https://doi.org/10.3390/machines13111056 - 14 Nov 2025

With the continuous increase in high-speed train operation speeds, lightweight bogie design has become a key means to enhance dynamic performance, which also increases the risk of structural fatigue. High-frequency wheel–rail excitations are transmitted to the bogie frame and couple with its higher-order [...] Read more.

With the continuous increase in high-speed train operation speeds, lightweight bogie design has become a key means to enhance dynamic performance, which also increases the risk of structural fatigue. High-frequency wheel–rail excitations are transmitted to the bogie frame and couple with its higher-order modes at around 200 Hz, inducing local high-frequency resonance. This coupling markedly increases the stress amplitude within the affected frequency range and accelerates vibration-induced fatigue damage. This study investigates the vibration fatigue characteristics of a bogie frame with an inner axle box under high-speed operation and wheel polygon wear conditions. Using a high-speed wheel–rail interaction test rig, dynamic stresses and the vibration acceleration of the bogie frame are measured under different speeds and polygon orders. Based on modal analysis and vibration fatigue methods, a high-frequency vibration fatigue assessment method for the bogie is developed. Wheel polygon significantly amplifies mid-to-high-frequency vibration energy, and for the bogie frame with an inner axle box, pronounced modal coupling is observed at around 200 Hz. In particular, under the 11th-order polygon condition, the equivalent stress at critical locations such as the traction motor seat weld seam exceeds the fatigue limit, while the effect of the 20th-order polygon is relatively mitigated. The proposed vibration fatigue assessment method provides a theoretical basis for the safe design and operational maintenance of high-speed trains with bogie frames with inner axle boxes. Full article

(This article belongs to the Special Issue Research and Application of Rail Vehicle Technology)

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18 pages, 3716 KB

Open AccessArticle

Time-Domain and Neural Network-Based Diagnosis of Bearing Faults in Induction Motors Under Variable Loads

by Hwi Gyo Lee, Seon Min Yoo, Wang Ke Hao and In Soo Lee

Machines 2025, 13(11), 1055; https://doi.org/10.3390/machines13111055 - 14 Nov 2025

Bearing faults are the most common type of failure in induction motors, given their long operating times and mechanical loads. Because induction motors in industrial environments operate under various load conditions, effective methods for diagnosing bearing faults across these conditions have become increasingly [...] Read more.

Bearing faults are the most common type of failure in induction motors, given their long operating times and mechanical loads. Because induction motors in industrial environments operate under various load conditions, effective methods for diagnosing bearing faults across these conditions have become increasingly important. Here, different load conditions were implemented with a powder clutch and a tension controller, and vibration data were acquired under both normal and faulty bearing conditions. To ensure diagnostic accuracy while improving time efficiency, a model bank-based fault diagnosis classifier is proposed, which utilizes independent classifiers trained for each load condition. For comparison, a single model-based classifier trained on all load conditions is also implemented. Both approaches are validated with three classifiers: support vector machine (SVM), multilayer neural network (MNN), and random forest (RF), with three input types: raw time-series signals, six statistical features, and three t-test–selected statistical features. Experimental results reveal that the model bank-based fault diagnosis classifier utilizing three statistical features selected by t-test maintained 98–100% accuracy while reducing operating time compared with Method 1 by 60.0, 71.2, and 60.0% for SVM, MNN, and RF, respectively. These results confirm that the proposed Method 2 utilizing time-domain analysis provides reliable and time-efficient performance for bearing fault diagnosis under variable load conditions. Full article

(This article belongs to the Special Issue Data-Driven Fault Diagnosis for Machines and Systems, 2nd Edition)

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18 pages, 4748 KB

Open AccessArticle

Effects of Inflow Deflection Angle on the Stall Formation Mechanism and Flow Field Structure in a Vertical Axial-Flow Pump

by Fan Meng, Qixiang Hu, Jinhe Liu, Yanjun Li, Guangjian Zhang and Jiaxing Lu

Machines 2025, 13(11), 1054; https://doi.org/10.3390/machines13111054 - 14 Nov 2025

The influence of inflow angle on the stall characteristics of a vertical axial flow pump is investigated numerically by solving the unsteady Reynolds-averaged Navier–Stokes equations. The study predicts both performance parameters and internal flow structures under varying inflow conditions. It is found that [...] Read more.

The influence of inflow angle on the stall characteristics of a vertical axial flow pump is investigated numerically by solving the unsteady Reynolds-averaged Navier–Stokes equations. The study predicts both performance parameters and internal flow structures under varying inflow conditions. It is found that as the deflection angle decreases, both the critical and deep stall points shift toward higher flow rates. For the −30° scheme, the design efficiency and design head decrease by 16.27% and increase by 19.59%, respectively, compared to the 0° scheme. As stall develops, an axisymmetric blockage region forms at the impeller inlet, which reduces axial velocity and increases the impeller’s angle of attack. Under design conditions, a smaller deflection angle exacerbates boundary layer separation near the blade leading edge, thereby weakening the local work capacity and intensifying turbulent dissipation. Furthermore, although a reduced deflection angle promotes an earlier onset of stall, it also leads to a decrease in the instability intensity of the stall flow field. These results reveal a critical trade-off: while a smaller deflection angle promotes an earlier stall onset, it effectively mitigates the intensity of stall instability, providing crucial guidance for optimizing the hydraulic design and operational stability of vertical axial flow pumps. Full article

(This article belongs to the Section Machine Design and Theory)

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17 pages, 10429 KB

Open AccessArticle

Development of a Simulation Computational Model for Hole Detection and Generation of Robot Tool Movement for Fitting Mold Preparation Nozzles

by Martin Pollák and Karol Goryl

Machines 2025, 13(11), 1053; https://doi.org/10.3390/machines13111053 - 14 Nov 2025

This article focuses on the design, development and optimization of a mechanical system with the aim of increasing the efficiency of the production process. The article describes the issues involved in the production of molds used for EPS (Expanded Polystyrene) and EPP (Expanded [...] Read more.

This article focuses on the design, development and optimization of a mechanical system with the aim of increasing the efficiency of the production process. The article describes the issues involved in the production of molds used for EPS (Expanded Polystyrene) and EPP (Expanded Polypropylene) materials, specifically the assembly of mold nozzles. Currently, the assembly of nozzles is performed manually, and the proposed solution aims to automate this process using software and robotics. The solution involves scanning the mounting holes and then modifying the mold model in Siemens NX, based on which a trajectory is generated in the virtual environment of RoboDK software. Communication between Siemens NX and RoboDK software is implemented via a Python algorithm using NXOpen and RoboDK API (Application Programming Interface) libraries. The proposed tool has flexible settings and is not dependent on a robotic arm or tool. The result is a prototype software tool for offline programming of automated assembly, which is adapted to different hole layouts, allowing its use in small-batch production in the future. The proposed tool has flexible settings and is not dependent on a specific robotic arm or tool. The solution was validated through comprehensive simulation testing in the RoboDK environment, demonstrating significant potential for time reduction and process optimization. Full article

(This article belongs to the Special Issue Advances in Computer-Aided Technology, 3rd Edition)

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22 pages, 12019 KB

Open AccessArticle

Study on Dynamic Characteristics and Key Gear Parameter Selection of the Cutting Gear Transmission System of Bauxite Mining Machine Under Overload Conditions

by Qiulai Huang, Weipeng Xu, Ziyao Ma, Ning Jiang, Yu Bu, Kuidong Gao and Xiaodi Zhang

Machines 2025, 13(11), 1052; https://doi.org/10.3390/machines13111052 - 14 Nov 2025

In certain mining areas, bauxite ore exhibits high and uneven hardness, causing frequent overloads in the cutting heads of bauxite mining equipment and challenging the dynamic performance and reliability of its gear transmission system. To investigate the influence of macro-geometric parameters, a dynamic [...] Read more.

In certain mining areas, bauxite ore exhibits high and uneven hardness, causing frequent overloads in the cutting heads of bauxite mining equipment and challenging the dynamic performance and reliability of its gear transmission system. To investigate the influence of macro-geometric parameters, a dynamic model was built using MASTA software (version 13.0.1). This study systematically analyzed the effects of pressure angle, face width, and bottom clearance coefficient on gear meshing characteristics, service life, and vibration noise under various loads. A preferred set of parameters was determined and validated through vibration and noise tests. The results show that increasing the pressure angle and face width improves gear meshing and fatigue life, while the bottom clearance coefficient has an optimal value of 0.4. Increasing the bottom clearance coefficient exacerbates vibration and noise, with other parameters causing fluctuations under different conditions. The optimal parameters of 23° pressure angle, 75 mm face width, and 0.4 bottom clearance coefficient effectively reduce vibration and noise, providing a theoretical and practical basis for improving the cutting transmission system. Full article

(This article belongs to the Section Machine Design and Theory)

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15 pages, 3120 KB

Open AccessArticle

Towards Sustainable Manufacturing: Particle Emissions in Milling Post-Processing of 3D-Printed Titanium Alloy

by Fahad M. Alqahtani, Mustafa Saleh, Abdelaty E. Abdelgawad, Ibrahim A. Almuhaidib and Faisal Alessa

Machines 2025, 13(11), 1051; https://doi.org/10.3390/machines13111051 - 13 Nov 2025

Electron beam melting (EBM) is an additive manufacturing method that enables the manufacturing of metallic parts. EBM-printed parts require post-processing to meet the surface quality and dimensional accuracy requirements. Machining is one approach that is beneficial for achieving these requirements. However, during machining, [...] Read more.

Electron beam melting (EBM) is an additive manufacturing method that enables the manufacturing of metallic parts. EBM-printed parts require post-processing to meet the surface quality and dimensional accuracy requirements. Machining is one approach that is beneficial for achieving these requirements. However, during machining, particles are emitted and can affect the environment and the operator’s health. This study aims to investigate the concentration of particles emitted during the milling of 3D-printed Ti6Al4V alloy produced by EBM. First, the influence of machining speed and cutting fluids, namely flood and minimum quantity lubricant (MQL), on particle emissions was statistically investigated. Then, the standby time required for the operator to safely open the machine door and interact with the machine within the machining area was studied. In this regard, two scenarios were proposed. In the first scenario, the machine door is open immediately after machining, and the operator waits until the particle concentration is acceptable. In the second, the machine door will be opened only when the particle concentration is acceptable. Statistical findings revealed that cutting fluids have a significant impact on particle emissions, exhibiting distinct patterns for both fine and coarse particles. Irrespective of the scenario, MQL results in higher particle concentration peaks and larger particle sizes, and the operator needs a longer standby time before interacting with the machine. For instance, the standby time in MQL is 328% more than that of the flood system. This study provides insight into sustainable manufacturing by taking into account social factors such as worker health and safety. Full article

(This article belongs to the Section Industrial Systems)

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28 pages, 34176 KB

Open AccessArticle

To Boldly Go: Redefining Mobility with Thrust-Augmented Rocker-Bogie CanBots for Simulated Planetary Exploration

by Carrington Chun and Muhammad Hassan Tanveer

Machines 2025, 13(11), 1050; https://doi.org/10.3390/machines13111050 - 13 Nov 2025

This research presents the first known example of a Thrust-Augmented Rocker Bogie (TARB). As a robust and passive mechanisms, the rocker bogie suspension system has seen widespread application in ground-based robotic planetary exploration rovers. However, with the first demonstration of a multirotor on [...] Read more.

This research presents the first known example of a Thrust-Augmented Rocker Bogie (TARB). As a robust and passive mechanisms, the rocker bogie suspension system has seen widespread application in ground-based robotic planetary exploration rovers. However, with the first demonstration of a multirotor on Mars, there is clearly a need to expand the locomotion capacity for planetary rovers. The TARB builds on the existing flight heritage of the rocker rogie but also innovatively combines the system with a multirotor configuration. The combined homogeneous mobility solution can successfully demonstrate multimodal mobility including in terrestrial, aerial, and hybrid forms of locomotion. The prototype TARB developed for this research was constructed in the form of a CanBot. CanBots provide a means to test space-oriented rover technologies with earth-based analogues. Three prototype multimodal CanBots are described in this work, with each showing improvements in mobility and overall design robustness. Laboratory validation of the final TARB-equipped CanBot showed that it could utilize the rocker-bogie system to engage complicated terrestrial terrains while also maintaining the capacity to fly as an aerial vehicle. The laboratory testing also indicated that the CanBot could climb significantly steeper slopes when employing the TARB in a hybrid mode, successfully climbing slopes of 60 degrees, demonstrating static stability on inclines of up to 90 degrees, and successfully navigating along fully inverted surfaces. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

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14 pages, 5315 KB

Open AccessArticle

Experimental Evaluation of Milling Post-Processing on the Surface Quality of MEX-Printed Carbon Fiber-Reinforced PLA Composites

by Abdullah Yahia AlFaify

Machines 2025, 13(11), 1049; https://doi.org/10.3390/machines13111049 - 13 Nov 2025

This study explores the machinability of Material Extrusion (MEX) printed parts made from carbon fiber-reinforced polylactic acid (PLA). MEX-printed parts typically exhibit high surface roughness, necessitating post-processing to enhance their quality. In this work, milling was used as a post-processing method to improve [...] Read more.

This study explores the machinability of Material Extrusion (MEX) printed parts made from carbon fiber-reinforced polylactic acid (PLA). MEX-printed parts typically exhibit high surface roughness, necessitating post-processing to enhance their quality. In this work, milling was used as a post-processing method to improve the surface finish. Response surface methodology (RSM) experimental design was employed to investigate the effects of cutting velocity, feed rate, and depth of cut on the surface quality of the machined surfaces. Results showed that the as-built MEX-printed sample exhibited a high average surface roughness (Sa) of ~7.982 µm, indicating the need for post-processing. Post-processing milling considerably enhances the Sa by reducing it to ~1.621 µm under the optimal condition. Statistical findings showed that all considered factors have significant influence on the Sa, with feed rate as the most influential one, contributing to 47.63% of the total variation. The Sa values varied from 1.834 µm to 4.146 µm due to changes in the considered factors. Increasing feed rate leads to the emergence of cavities and ridges along the deposited filaments associated with brittle removal mechanism, resulting in higher surface roughness. Full article

(This article belongs to the Special Issue Recent Advances in Surface Integrity with Machining and Milling)

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30 pages, 11506 KB

Open AccessArticle

A Health-Aware Fuzzy Logic Controller Optimized by NSGA-II for Real-Time Energy Management of Fuel Cell Electric Commercial Vehicles

by Juan Du, Xuening Zhang, Shanglin Wang and Xiaodong Liu

Machines 2025, 13(11), 1048; https://doi.org/10.3390/machines13111048 - 13 Nov 2025

This study introduces a health-aware fuzzy logic (FL) energy management strategy (EMS) for fuel cell electric commercial vehicles (FCECVs) that aimed to improve energy efficiency and extending fuel cell system (FCS) lifespan. The FL-based EMS was developed using vehicle power demand and battery [...] Read more.

This study introduces a health-aware fuzzy logic (FL) energy management strategy (EMS) for fuel cell electric commercial vehicles (FCECVs) that aimed to improve energy efficiency and extending fuel cell system (FCS) lifespan. The FL-based EMS was developed using vehicle power demand and battery state of charge (SOC) as inputs, with the FCS power change rate as the output, aiming to mitigate degradation induced by abrupt load transitions. A multi-objective optimization framework was established to optimize the fuzzy logic controller (FLC) parameters, achieving a balanced trade-off between fuel economy and FCS longevity. The non-dominated sorting genetic algorithm-II (NSGA-II) was utilized for optimization across various driving cycles, with average Pareto-optimal solutions employed for real-time application. Performance evaluation under standard and stochastic driving cycles benchmarked the proposed strategy against dynamic programming (DP), charge-depletion charge-sustaining (CD-CS), conventional FL strategies, and a non-optimized baseline. Results demonstrated an approximately

38 %

reduction in hydrogen consumption (HC) relative to CD-CS and over

75 %

improvement in degradation mitigation, with performance superior to that of DP. Although the strategy exhibits an average

17.39 %

increase in computation time compared to CD-CS, the average single-step computation time is only

2.1

ms, confirming its practical feasibility for real-time applications. Full article

(This article belongs to the Special Issue Energy Storage and Conversion of Electric Vehicles)

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20 pages, 11501 KB

Open AccessArticle

The Influence of Suspension Elastokinematics on Vehicle Handling and Stability

by Albert Basiul, Vidas Žuraulis, Robertas Pečeliūnas and Saugirdas Pukalskas

Machines 2025, 13(11), 1047; https://doi.org/10.3390/machines13111047 - 12 Nov 2025

This study investigates the influence of suspension elastokinematics on vehicle handling and stability through a combined research of experimental testing and numerical simulation. Laboratory tests were conducted on the front suspension of a Mercedes-Benz S320 using a quarter-car test rig equipped with specialized [...] Read more.

This study investigates the influence of suspension elastokinematics on vehicle handling and stability through a combined research of experimental testing and numerical simulation. Laboratory tests were conducted on the front suspension of a Mercedes-Benz S320 using a quarter-car test rig equipped with specialized sensors to measure wheel displacements, steering angles, camber, and accelerations. Complementary dynamic tests were carried out under real driving conditions, including braking in a turn and “fishhook” maneuvers, to capture suspension behavior under critical operating scenarios. Based on the experimental data, an MSC Adams/Car multibody simulation model was used, incorporating varying stiffness values of suspension elastomeric elements that replicated progressive aging and degradation effects. The simulation results were compared with experimental data to validate the model’s predictive capability. Key findings indicate that reductions in elastomer stiffness significantly affect wheel kinematics, vehicle yaw response, and lateral acceleration, particularly during high-intensity maneuvers. The results underline the critical importance of accounting for elastomeric component degradation in suspension modeling to ensure vehicle safety and performance over the operational lifespan. The developed methodology demonstrates the effectiveness of integrating experimental measurements with advanced simulation tools to assess elastokinematic effects on vehicle dynamics. Full article

(This article belongs to the Special Issue Advances in Vehicle Suspension System Optimization and Control)

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14 pages, 5353 KB

Open AccessArticle

Slot Number Optimization for Motorcycle Traction Motor Considering Driving Duty Cycle

by Yang Gu, Hui Yi, Huimin Ouyang, Lei Mei, Qiang Sun and Zichong Zhu

Machines 2025, 13(11), 1046; https://doi.org/10.3390/machines13111046 - 12 Nov 2025

Due to their compact dimensions, high torque density, high efficiency, and superior flux-weakening capabilities, permanent magnet synchronous machines with tooth-coil winding (TC-PMSMs) are highly suitable for low-power electric transportation applications. This study incorporates the actual duty cycle of an electric motorcycle in the [...] Read more.

Due to their compact dimensions, high torque density, high efficiency, and superior flux-weakening capabilities, permanent magnet synchronous machines with tooth-coil winding (TC-PMSMs) are highly suitable for low-power electric transportation applications. This study incorporates the actual duty cycle of an electric motorcycle in the optimization of the slot number for the drive machine. The proposed methodology addresses the shortcomings of conventional design strategies, which typically consider only a limited set of operating points, leading to suboptimal round-trip efficiency under real driving conditions. Firstly, the influence of slot number on torque output, electromagnetic losses, and flux-weakening performance is examined for 10-pole TC-PMSMs using finite element analysis. Subsequently, the optimal slot number is identified by integrating the real duty cycle of the drive motor into the evaluation. To verify the accuracy and effectiveness of the analytical results and design approach, prototypes of stator assemblies with varying slot numbers were fabricated and experimentally tested. Full article

(This article belongs to the Section Electrical Machines and Drives)

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25 pages, 4586 KB

Open AccessArticle

Ball Mill Load Classification Method Based on Multi-Scale Feature Collaborative Perception

by Saisai He, Zhihong Jiang, Wei Huang, Lirong Yang and Xiaoyan Luo

Machines 2025, 13(11), 1045; https://doi.org/10.3390/machines13111045 - 12 Nov 2025

Against the backdrop of intelligent manufacturing, the ball mill, as a key energy-consuming piece of equipment, requires an accurate perception of its load state, which is crucial for optimizing production efficiency and ensuring operational safety. However, its vibration signals exhibit typical nonlinear and [...] Read more.

Against the backdrop of intelligent manufacturing, the ball mill, as a key energy-consuming piece of equipment, requires an accurate perception of its load state, which is crucial for optimizing production efficiency and ensuring operational safety. However, its vibration signals exhibit typical nonlinear and non-stationary characteristics, intertwined with complex noise, posing significant challenges to high-precision identification. A core contradiction exists in existing diagnostic methods: convolution network-based methods excel at capturing local features but overlook global trends, while Transformer-type models, although capable of capturing long-range dependencies, tend to “average out” critical local transient information during modeling. To address this dilemma, this paper proposes a new paradigm for multi-scale feature collaborative perception. This paradigm is implemented through an innovative deep learning architecture—the Residual Block-Swin Transformer Network (RB-SwinT). This architecture subtly achieves hierarchical and in-depth integration of the powerful global context modeling capability of Swin Transformer and the excellent local detail refinement capability of the residual module (ResBlock), enabling synchronous and efficient representation of both the macro trends and micro mutations of signals. On the experimental dataset covering nine types of fine operating conditions, the overall recognition accuracy of the proposed method reaches as high as 96.20%, which is significantly superior to a variety of mainstream models. To further verify the model’s generalization ability, this study was tested on the CWRU public bearing fault dataset, achieving a recognition accuracy of 99.36%, which outperforms various comparative methods such as SAVMD-CNN. This study not only provides a reliable new technical approach for ball mill load identification but also demonstrates its practical application value in indicating critical operating conditions and optimizing production operations through an in-depth analysis of the physical connotations of each load level. More importantly, its “global-local” collaborative modeling concept opens up a promising technical path for processing a broader range of complex industrial time-series data. Full article

(This article belongs to the Section Advanced Manufacturing)

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27 pages, 6674 KB

Open AccessArticle

Design and Development of an Autonomous Mobile Robot for Unstructured Indoor Environments

by Ameur Gargouri, Mohamed Karray, Bechir Zalila and Mohamed Ksantini

Machines 2025, 13(11), 1044; https://doi.org/10.3390/machines13111044 - 12 Nov 2025

This research work presents the design and the development of a cost-effective autonomous mobile robot for locating misplaced objects within unstructured indoor environments. The tools integrated into the proposed system for perception and localization are a hardware architecture equipped with LiDAR, an inertial [...] Read more.

This research work presents the design and the development of a cost-effective autonomous mobile robot for locating misplaced objects within unstructured indoor environments. The tools integrated into the proposed system for perception and localization are a hardware architecture equipped with LiDAR, an inertial measurement unit (IMU), and wheel encoders. The system also includes an ROS2-based software stack enabling autonomous navigation via the NAV2 framework and Adaptive Monte Carlo Localization (AMCL). For real-time object detection, a lightweight YOLO11n model is developed and implemented on a Raspberry Pi 4 to enable the robot to identify common household items. The robot’s motion control is achieved by a fuzzy logic-enhanced PID controller that dynamically modifies gain values based on navigation conditions. Remote supervision, task management, and real-time status monitoring are provided by a user-friendly Flutter-based mobile application. Simulations and real-world experiments demonstrate the robustness, modularity, and responsiveness of the robot in dynamic environments. This robot achieves a 3 cm localization error and a 95% task execution success rate. Full article

(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics, Second Edition)

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21 pages, 13092 KB

Open AccessArticle

Study on the Influence of the Mechanical Characteristics of the Cutting-Type Anti-Climbing Energy Absorber on the Collision Behavior of the GFRP Head Cover for Subways

by Xuan Liu, Ping Xu, Yifan Hu, Ying Gao and Dongtao Wang

Machines 2025, 13(11), 1043; https://doi.org/10.3390/machines13111043 - 12 Nov 2025

Anti-climbing energy absorbers (AEAs) are often installed at the ends of subway vehicles to prevent climbing in the event of a head-on collision or rear-end collision, thereby improving safety performance. To reduce the air resistance of the vehicle during operation, the AEA is [...] Read more.

Anti-climbing energy absorbers (AEAs) are often installed at the ends of subway vehicles to prevent climbing in the event of a head-on collision or rear-end collision, thereby improving safety performance. To reduce the air resistance of the vehicle during operation, the AEA is usually wrapped with the GFRP head cover. However, the collision behavior of the head cover during a collision requires further research. The effects of mechanical properties of cutting anti-climbing energy absorbers (CAEAs) on the collision behavior of glass fiber reinforced polymer (GFRP) head covers for subway vehicles are investigated in this study. Firstly, the force–displacement curve of the CAEA was obtained through a dynamic impact test, and the finite element (FE) model of the CAEA with a GFRP head cover was constructed and verified. Subsequently, the effects of the four mechanical characteristics of the CAEA (i.e., initial peak crushing force (IPCF), platform force, compaction force, and eccentric height difference) on the collision behavior of the GFRP head cover were systematically analyzed. The results show that the increase in IPCF improves the energy absorption of CAEA, but that damage and stress concentration of the head cover at the moving end also occur. The increase in platform force induced the premature fracture of the GFRP head cover. The collision behavior of the head cover reaches a critical value when the compaction force is between 2500 and 3000 kN. Increasing the eccentric height difference between the anti-climbing teeth weakens the cutting energy absorption efficiency of CAEA and changes its deformation mode. This study can provide important insights into the design and optimization of anti-climbing energy absorbers for subway vehicles, and has important engineering value for improving the durability of the head cover and the collision safety of the vehicle. Full article

(This article belongs to the Section Advanced Manufacturing)

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16 pages, 4287 KB

Open AccessArticle

A Woven Soft Wrist-Gripper Composite End-Effector with Variable Stiffness: Design, Modeling, and Characterization

by Pan Zhou, Yangzuo Liu, Junxi Chen, Haoyuan Chen, Haili Li and Jiantao Yao

Machines 2025, 13(11), 1042; https://doi.org/10.3390/machines13111042 - 11 Nov 2025

Soft robots often suffer from insufficient load capacity due to the softness of their materials. Existing variable stiffness technologies usually introduce rigid components, resulting in decreased flexibility and complex structures of soft robots. To address these challenges, this work proposes a novel wrist-gripper [...] Read more.

Soft robots often suffer from insufficient load capacity due to the softness of their materials. Existing variable stiffness technologies usually introduce rigid components, resulting in decreased flexibility and complex structures of soft robots. To address these challenges, this work proposes a novel wrist-gripper composite soft end-effector based on the weaving jamming principle, which features a highly integrated design combining structure, actuation, and stiffness. This end-effector is directly woven from pneumatic artificial muscles through weaving technology, which has notable advantages such as high integration, strong performance designability, lightweight construction, and high power density, effectively reconciling the technical trade-off between compliance and load capacity. Experimental results demonstrate that the proposed end-effector exhibits excellent flexibility and multi-degree-of-freedom grasping capabilities. Its variable stiffness function enhances its ability to resist external interference by 4.77 times, and its grasping force has increased by 1.7 times, with a maximum grasping force of 102 N. Further, a grasping force model for this fiber-reinforced woven structure is established, providing a solution to the modeling challenge of highly coupled structures. A comparison between theoretical and experimental data indicates that the modeling error does not exceed 7.8 N. This work offers a new approach for the design and analysis of high-performance, highly integrated soft end-effectors, with broad application prospects in unstructured environment operations, non-cooperative target grasping, and human–robot collaboration. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

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20 pages, 3141 KB

Open AccessArticle

Solid Lubricants for the Wheel–Rail Interface: Practical Experience and Computational Estimation of Their Effects

by Tomáš Michálek, Petr Voltr, Stanislava Liberová and Jiří Šlapák

Machines 2025, 13(11), 1041; https://doi.org/10.3390/machines13111041 - 11 Nov 2025

This paper deals with solid lubricants for the wheel–rail interface; the topic is viewed from two different but complementary perspectives. By means of simulations, the potential contribution of these lubricants, applied for purposes of wheel flange lubrication on curved tracks, to the reduction [...] Read more.

This paper deals with solid lubricants for the wheel–rail interface; the topic is viewed from two different but complementary perspectives. By means of simulations, the potential contribution of these lubricants, applied for purposes of wheel flange lubrication on curved tracks, to the reduction in the wheel–rail wear level is estimated. Further, the relationship between frictional work in wheel–rail contact and guiding forces is investigated. The aim of this paper is to contribute to the knowledge of a physical basis for this relationship and to help understand the capability of these quantities to quantify the damaging effects of running vehicles on curved tracks. The mechanism of the observed increase in quasi-static guiding force on the leading wheel with lubricated wheel flanges is described in detail, using different quantities characterizing the steady running of a vehicle through a curve. The limitation of the contribution of wheel flange lubrication to the reduction in total frictional power on all wheels of the vehicle is also explained. In the second part, attention is paid to a practical assessment of the performance of solid lubricant samples using the testing methodology of the European standards EN 15427-2-1 and EN 16028. The aim of this part of the paper is to summarize the authors’ experience with twin-disc machine measurements, showing imperfections in the standardized testing methodology, as well as the significantly different performance of various solid lubricant samples, which is influenced by many factors. Based on their experience, further research on solid lubricant performance using wheel–rail roller rigs is outlined. Full article

(This article belongs to the Section Friction and Tribology)

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23 pages, 2408 KB

Open AccessArticle

Chain-Based Outlier Detection: Interpretable Theories and Methods for Complex Data Scenarios

by Huiwen Dong, Meiliang Liu, Shangrui Wu, Qing-Guo Wang and Zhiwen Zhao

Machines 2025, 13(11), 1040; https://doi.org/10.3390/machines13111040 - 11 Nov 2025

Outlier detection is a critical task in the intelligent operation and maintenance (O&M) of transportation equipment, as it helps ensure the safety and reliability of systems like high-speed trains, aircraft, and intelligent vehicles. Nearest neighbor-based detectors generally offer good interpretability, but often struggle [...] Read more.

Outlier detection is a critical task in the intelligent operation and maintenance (O&M) of transportation equipment, as it helps ensure the safety and reliability of systems like high-speed trains, aircraft, and intelligent vehicles. Nearest neighbor-based detectors generally offer good interpretability, but often struggle with complex data scenarios involving diverse data distributions and various types of outliers, including local, global, and cluster-based outliers. Moreover, these methods typically rely on predefined contamination, which is a critical parameter that directly determines detection accuracy and can significantly impact system reliability in O&M environments. In this paper, we propose a novel chain-based theory for outlier detection with the aim to provide an interpretable and transparent solution for fault detection. We introduce two methods based on this theory: Cascaded Chain Outlier Detection (CCOD) and Parallel Chain Outlier Detection (PCOD). Both methods identify outliers through sudden increases in chaining distances, with CCOD being more sensitive to local data distributions, while PCOD offers higher computational efficiency. Experimental results on synthetic and real-world datasets demonstrate the superior performance of our methods compared to existing state-of-the-art techniques, with average improvements of 11.3% for CCOD and 14.5% for PCOD. Full article

(This article belongs to the Section Machines Testing and Maintenance)

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21 pages, 4092 KB

Open AccessArticle

Design and Experiment of a Roller-Brush Type Harvesting Device for Dry Safflower Based on Plant Clamping and Pose Adjustment

by Chunjiao Ma, Haifeng Zeng, Yun Ge, Guotao Li, Botao He and Yangyang Guo

Machines 2025, 13(11), 1039; https://doi.org/10.3390/machines13111039 - 11 Nov 2025

To address the challenges of low efficiency and high damage rates in dryland safflower harvesting, a roller-brush type harvesting device was developed. The design was developed following a detailed analysis of the spatial distribution and mechanical characteristics of safflower plants. The pose adjustment [...] Read more.

To address the challenges of low efficiency and high damage rates in dryland safflower harvesting, a roller-brush type harvesting device was developed. The design was developed following a detailed analysis of the spatial distribution and mechanical characteristics of safflower plants. The pose adjustment process begins with helical grooves clamping and contacting the plant stem. The propulsion action of the helix then forces the stem to undergo a predetermined deflection displacement. The optimal picking pose occurs when the plant’s longitudinal axis is perpendicular to the rotational axis of the picking roller brush. In this position, the picking roller brush shears the filaments at the necking zone through gentle contact with the fruit balls. This mechanism transforms the traditional pull-off separation into a low-damage shear-separation mode. The Box–Behnken test was designed to find the optimal combination of parameters for picking: picking roller brush speed of 282.5 r/min, roller brush spacing of 3.7 mm, and brush bristle diameter of 0.1 mm. Verification tests showed the picking, damage and fruit injury rates were 92.4%, 7.1% and 1.2%, respectively, with standard deviations of 5.42%, 0.51%, and 0.08%. The harvesting efficiency reached 0.053 hm²/h, 8.48 to 12.01 times higher than manual harvesting. Full article

(This article belongs to the Section Machine Design and Theory)

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33 pages, 3270 KB

Open AccessArticle

Design-Orientated Optimization and Motion Planning of a Parallel Platform for Improving Performance of an 8-DOF Hybrid Surgical Robot

by Asna Kalsoom, Muhammad Faizan Shah, Zareena Kausar, Faizan Khan Durrani, Syed Zahid Hussain and Muhammad Umer Farooq

Machines 2025, 13(11), 1038; https://doi.org/10.3390/machines13111038 - 9 Nov 2025

The emergence of surgical robots has revolutionized complex operations, improving precision, lowering operating risks, and shortening recovery periods. Given the merits, an eight degrees of freedom (DOF) hybrid surgical robot (HSR) has been proposed, which leverages the benefits of both serial and parallel [...] Read more.

The emergence of surgical robots has revolutionized complex operations, improving precision, lowering operating risks, and shortening recovery periods. Given the merits, an eight degrees of freedom (DOF) hybrid surgical robot (HSR) has been proposed, which leverages the benefits of both serial and parallel manipulators. However, its performance is hindered by the constrained range of motion of its parallel platform. To address the issue, this research presents a systematic approach for designing and optimizing the proposed HSR. The first step is the design of the HSR, followed by a multi-stage design analysis of its parallel platform, concentrating on kinematic, geometrical, and singularity analysis. Higher values of the condition number indicate singular configurations in the platform’s workspace, highlighting the need for an optimized design. For optimization of the platform, performance parameters like global condition number (GCN), actuator forces, and stiffness are identified. Initially, the design is optimized by targeting GCN only through a genetic algorithm (GA). This approach compromised the other parameters and raised the need for simultaneous optimization employing a non-dominated sorting genetic algorithm (NSGA II). It offered a better trade-off between performance parameters. To further assess the working of the optimized parallel platform, workspace analysis and motion planning of a predefined trajectory have been performed. Full article

(This article belongs to the Special Issue Mechanical Design of Parallel Manipulators)

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18 pages, 7174 KB

Open AccessArticle

Stress–Strain Evolution and Multi-Pass Process Optimization in Mandrel-Free Hot Spinning of Wind Tunnel Nozzles

by Piyao Liu, Linsen Song, Zhenhui Li, Wei Liang, Ziwei Jiang, Xiaosha Tang, Qiang Gao and Shuang Guo

Machines 2025, 13(11), 1037; https://doi.org/10.3390/machines13111037 - 9 Nov 2025

Traditional manufacturing methods of wind tunnel nozzles are often cumbersome, time-consuming, and costly. The study of spinning forming technology for wind tunnel nozzles provides a pathway to improve manufacturing efficiency while reducing both cost and production cycle. However, when processing alloy steel (20MnMo), [...] Read more.

Traditional manufacturing methods of wind tunnel nozzles are often cumbersome, time-consuming, and costly. The study of spinning forming technology for wind tunnel nozzles provides a pathway to improve manufacturing efficiency while reducing both cost and production cycle. However, when processing alloy steel (20MnMo), challenges arise due to large deformation, high-temperature loading, and complex wall-thickness control. To address these issues, this work proposes a die-less multi-pass hot spinning process. A three-dimensional dynamic explicit finite element model was developed to simulate the stress–strain evolution during multi-pass spinning. In the first pass, an L9 orthogonal experimental design was applied to analyze the influence of spinning parameters on forming stress and plastic deformation capacity, thereby determining the optimal combination of workpiece rotation speed, axial feed, and radial feed rates. The optimized design strategy was subsequently extended to ten passes. Based on simulation results, hot spinning experiments were conducted, followed by precision machining of the nozzle’s inner and outer surfaces. Inspection results indicated that the deviations in contour and wall thickness between simulation predictions and actual specimens were both less than 0.5%. This study establishes an integrated process route combining numerical simulation, hot spinning, and finishing, providing both theoretical support and practical guidance for the high-precision and high-stability manufacturing of complex thin-walled nozzle structures. Full article

(This article belongs to the Section Machine Design and Theory)

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