Machines, Volume 11, Issue 9 (September 2023) – 73 articles

Platooning is generally known as a control method for driving a group of connected and automated vehicles in motorway context. Nevertheless, platoon control might also work on urban roads. One possible strategy to increase overall road traffic performance and to reduce congestion in urban traffic networks is to combine platooning with traffic signal control at intersections. The traffic flow can be maximized with coordinated scheduling of traffic signals together with platooning activities, resulting in decreased travel times and fuel consumption. This paper investigates several aspects of this combined control, such as the procedures for coordination and communication between platooning vehicles and traffic signals. Efficient algorithms are suggested to optimize platoon formation and dissolution at junctions and to change traffic signal phases depending on platoon arrival and departure times. The proposed solutions have been tested and verified with SUMO, a high-fidelity microscopic traffic simulator. Full article

This paper presents the new synthesis models of spatial linkages for designing measurement motion functions and ranges and identifying the actual dimension parameters. The spatial five-bar linkage is first introduced for the kinematic model of a double ball bar test of a two-axis rotary table. To design the ideal measurement motion and motion range of the double ball bar test, a novel saddle synthesis model of a spatial four-bar linkage RRSS is readily presented. Based on the output data measured from the double ball bar test, a new saddle synthesis model of a spatial five-bar linkage RRSPS is logically proposed for identifying their actual dimensions. Finally, three test cases and their results indicate that the new synthesis models presented in the paper can conveniently and efficiently calculate the measurement motion function and range and accurately identify the actual dimensions of the double ball bar test, which provides a suitable mathematical model for improving the accuracy of the double ball bar tests of a two-axis rotary table of machine tools. Full article

The teleoperation feature of a leader–follower robot is used to operate the robot in a working environment that is dangerous to the operator. This paper proposes a method for estimating the intended operation of the operator of the leader–follower robot and generating behaviors for the follower robot. By generating partially autonomous robot behavior, our proposed method decreases the burden on the operator and realizes a safe controller that is robust against misoperation or disturbances. Owing to the impact of misoperation on estimation and the potential for unintended movement of the follower robot, our proposed estimation method relies on historical values of intended operation. The proposed method was verified through simulation using real operation inputs to the leader system based on practical scenarios, including misoperation. Full article

The landing buffer mechanism (LBM) is a crucial component of aerospace landing explorations, determining the success of the entire mission. Reliability demonstration tests (RDTs) are required to ensure the LBM’s performance meets the design index. However, the RDTs of the LBM often encounter limited samples and zero-failure data, making traditional binominal test programs and reliability assessment methods based on the maximum likelihood theory unsuitable. This paper introduces a novel small-sample test verification method for the LBM, which transforms traditional binominal tests into more informative metrological tests by measuring the buffer strokes of the LBM’s subsystems. Furthermore, a confidence limit theory for the product of subsystem reliability is developed in conjunction with the reliability series model of the LBM. This theory can use the measurement data of subsystems to assess the confidence limit of the LBM’s reliability. An actual engineering application demonstrates that the proposed method can effectively handle zero-failure data and verifies that the LBM’s reliability exceeds 0.9999 with a confidence of 0.9. Full article

In Industry 4.0., robots are regarded as one of the key components. In recent years, collaborative robots (cobots) have risen in relevance and have been included in the industry to perform tasks alongside humans. Robots have been used in many applications in manufacturing processes; for the scope of this paper, the emphasis on these applications is centered on welding and gluing. These applications need to be performed with specific speed, efficiency, and accuracy to attain optimal welding or bonding to the pieces. An operator cannot maintain such conditions consistently, with minimum variations, for an extended period; hence, robots are a more suitable option to perform those tasks. The robots used for these applications need to be instructed to follow a trajectory to either weld or apply the glue. This path must be programmed on the robot by an operator, and depending on the complexity of the trajectory, it can take up to extended periods of time to set all the required waypoints. There are specialized software environments that contribute to the automation of these tasks; however, the overall cost of the licenses is not affordable if the scale of the project only requires developing and programming trajectories a few times. This paper contains a proposal for an open-source Computer Aided Manufacturing (CAM) software to automatically generate the trajectories needed for the aforementioned welding and gluing applications. The procedure to develop the software starts by selecting the surface that will be welded or to which glue will be applied. The surface determines the model of the trajectory to be followed. Next, a processing system is fed with the individual points that make up the trajectory provided by their selection over the Computer Aided Drawing (CAD) model. This system then creates a program based on URScript^® that can be directly uploaded to and executed on the robot. A set of tests is presented to validate the applications and to demonstrate the versatility of the developed trajectory generation system. Full article

This paper proposes an adaptive shift schedule design framework based on dynamic programming (DP) algorithm and fuzzy logical control to promote the shift schedule’s adaptability whilst improving the comprehensive performance of the multi-gear automated manual transmission (AMT) electric vehicles in real-time application. First, the DP algorithm is employed to extract an offline optimal gear-shift schedule based on a set of driving conditions, including 11 groups of typical driving cycles. Second, a fuzzy logical controller is formulated considering the variation in the vehicle load and acceleration, where a velocity increment is exported online to adjust the gear-shift velocity of the predesigned DP-based schedule to develop a Fuzzy-DP shift schedule. In addition, multi-objective particle swarm optimization (MOPSO) is utilized to construct a comprehensive shift schedule by simultaneously considering the dynamic and economic performance of the vehicle. Then, the dynamic and economic shift schedules are deployed as the benchmark to examine the performance of the proposed shift schedule. Finally, the effectiveness of the Fuzzy-DP shift schedule is evaluated by comparison with others under various combined driving cycles (including vehicle load and velocity). The comparisons demonstrate the remarkable promotion in the adaptability of the Fuzzy-DP shift schedule in terms of acceleration time, energy-saving potential, and shift frequency. The most significant improvements in the dynamic, economic, and shift frequency can reach 8.86%, 10.12%, and 8.56%, respectively, in contrast to the MOPSO-based shift schedule. Full article

Periodic elastic metamaterials (EMMs) display the capability to forbid the transmission of elastic waves for certain frequency ranges, leading to band gaps. If topology optimization strategies are exploited to tune the band gaps of EMMs, the said band gaps cannot be modified in real-time. This limitation can be overcome by allowing for active materials in the design of EMMs. In this work, a hyperelastic piezoelectric composite was considered to assess the coupled effects of material and geometric nonlinearities on the behavior of sculptured microstructures featuring a three-dimensional periodicity. Specifically, it was assumed that the composite material is obtained by embedding piezo nanoparticles into a soft polymeric matrix. In this way, piezoelectricity and instability-induced pattern transformation could be fully exploited to actively tune the band gaps. A thermodynamically consistent multi-physics model for the active composite material is discussed and implemented in a general-purpose finite-element code. The reported results of the simulations showed how the band gaps are affected by the aforementioned nonlinearities and by a feature of the architected periodic cell linked to its topology. Full article

The peristaltic in-pipe robot incorporates multiple actuators, and achieving precise cooperative control among these actuators poses significant complexity. To address these issues, the Theory of Inventive Problem Solving (TRIZ) is applied to identify and resolve physical and technical conflicts in the creative design process of peristaltic in-pipe robots. By highlighting the insights on and technical guidance offered by TRIZ’s inventive principles, this paper examines the method for realizing a single-motor-driven peristaltic in-pipe robot from a transmission perspective. By employing a combination of connecting rods, cam mechanisms, and gear systems, a one-DOF peristaltic in-pipe robot was devised. Subsequently, a prototype was constructed, and successful bidirectional motion tests were conducted within pipes. The findings highlight the efficacy of the TRIZ-based design approach in innovatively designing one-DOF in-pipe robots and the unnecessary employment of complex multi-drive cooperative control in peristaltic in-pipe robots. Full article

The arc sound signal is one of the most important aspects of information related to pattern identification regarding the penetration state of ship robotic GMAW; however, arc sound is inevitably affected by noise interference during the signal acquisition process. In this paper, an improved wavelet threshold denoising method is proposed to eliminate interference and purify the arc sound signal. The non-stationary random distribution characteristics of GMAW noise interference are also estimated by using the high-frequency detail coefficients in different domains after wavelet transformation, and a mode of measuring scale that is logarithmically negatively correlated with the wavelet decomposition scale is created to update the threshold. The gradient convergent threshold function is established using the natural logarithmic function structure and concave–convex gradient to enable the nonlinear adjustment of the asymptotic rate. Further, some property theorems related to the optimized threshold function are proposed and theoretically proven, and the effectiveness and adaptability of the improved method are verified via the denoising simulation of speech synthesis signals. The four traditional denoising methods and our improved version are applied in the pretreatment of the GMAW arc sound signal, respectively. Statistical analysis and short-time Fourier transform are used to extract eight-dimensional time and frequency domain feature parameters from the denoised signals with randomly time-varying characteristics, and the extracted joint feature parameters are used to establish a nonlinear mapping model of penetration state identification for ship robotic GMAW using the pattern classifiers of RBFNN, PNN and PSO-SVM. The simulation results yielded by visual penetration classification and the multi-dimensional evaluation index of the confusion matrix indicate that the improved denoising method proposed in this paper achieves a higher accuracy in the extraction of penetration state features and greater precision in the identification of pattern classification. Full article

This paper analyzes the performance of Kalman filter-based estimators for robust filtering and rotor asymmetry detection in wound rotor induction machines (WRIMs) using real-time data. Filter models were designed based on an extended model of WRIMs. The detection of rotor asymmetry was achieved by estimating the states of rotor resistance and speed using four filters. The sensitivity of the parameters under healthy and asymmetry conditions was thoroughly analyzed and categorized as low, medium, and high sensitivity parameters. Robust model-based estimators were designed to minimize the probability of false alarms. The performance analysis demonstrated that the dual unscented Kalman filter (DUKF) outperformed other Kalman filters such as the extended Kalman filter (EKF), dual extended Kalman filter (DEKF), and unscented Kalman filter (UKF) for state estimation of WRIM. Full article

In ultra-precision machining (UPM), position-independent geometric errors (PIGEs), i.e., squareness errors, have a crucial impact upon the form accuracy of a machined surface. Accordingly, more research work has been conducted in PIGE identification, to improve the form accuracy. However, the general identification methods were developed without consideration of the specific squareness errors for crucial PIGEs under the form errors of the machining process. Therefore, a new method with featured structures was proposed, to identify crucial PIGEs in UPM. Firstly, a volumetric error model was developed for PIGEs, to discuss the relationship between squareness errors and their resulting machining form errors. Secondly, following the developed model, some featured structures have been proposed with their machining form errors, to significantly indicate crucial PIGEs. Finally, a series of UPM and measuring experiments were conducted for the featured structures, and then their machining form errors were measured and extracted with specific squareness errors for the identification of crucial PIGEs. The theoretical and experimental results revealed that the proposed method is simple and efficient with the featured structures to accurately identify crucial PIGEs in UPM. Significantly, the study offers a deep insight into high-quality fabrication in UPM. Full article

In studies of dynamic stability and power quality, it is necessary to know the values of the mechanical parameters determining the transient response of wind turbines. Their exact values are not as decisive as the power curve, but an inaccurate estimate can distort or even invalidate the simulation results. From a review of the literature, it has been found that, despite their importance, the values of inertia, stiffness and damping are hardly available for any turbine model. Another detected problem is the lack of confidence in the data origin. This article aims to solve the issue of the scarcity and unreliability of data on inertia, and gathers the information found on the remaining mechanical parameters. Available blade inertia values in kg · m${}^2$ are presented. Special treatment has been given to those providing the mass distribution along the blade span, for which the provided values of inertia have been compared with those obtained numerically, showing good matching. With this, different reliable relations are obtained that allow for the calculation of the turbine rotor inertia, based on the mass and length of the blade. When the center of gravity is also available, a very correlated expression ($r^2=0.975$) is provided to obtain the inertia. The references to the stiffness and damping constant of the drive train, which are even more rare, will also be presented. In addition, the study includes a revision of gearboxes, generators and blade weight, according to their IEC-class and material. Full article

Available hydropneumatic suspension simulation test benches have insufficient loading accuracy and limited functionality rendering them unsuitable for performance testing of heavy vehicles with this type of suspension. Therefore, a multi-functional compound simulation test bench was designed that used an electro-hydraulic proportional control technique. A mathematical model was established to describe the hydraulic loading system, and the transfer function of the system was derived. The gain and phase margins confirmed the stability of the system. A simulation model was established in the Simulink environment and step and sine signals of different frequencies were applied separately to analyze the dynamic characteristics of the system. The results showed that the system responded slowly and exhibited phase lag and signal distortion. The dynamic characteristics of the system were improved by incorporating an adaptive fuzzy PID controller. Simulation results showed that the response of the system to the step signal stabilized at the preset value within 0.3 s with no oscillation or overshoot. The improved system performed well in replicating the random vibrations of heavy vehicles operating on Class B and C roads. This confirmed that the system can satisfy the loading requirements of heavy vehicle hydropneumatic suspensions and can be used as a simulation test bench for such suspensions. Full article

In electrical discharge machining (EDM), the tool electrode is one of the substantial components of the system, and it ensures the success or failure of the EDM process. The electrode’s role is to conduct electrical charges and erode the workpiece to the desired shape. Different electrode materials have different impacts on machining. Certain electrode materials remove metal quickly but wear out rapidly, while others degrade slowly but the material removal is too slow. The choice of the electrode has an influence on both the mechanical properties, such as metal removal rate (MRR), wear rate, surface finish, surface modification and machinability, and the electrical properties, such as sparking initiation, time lag, gap contamination and process stability. There are factors to consider when fabricating an electrode, which include the type of workpiece materials, the metallurgical alloying of the materials, the choice of fabrication techniques, the intended use of the electrode, and material cost. Considerable challenges in EDM electrode fabrication have been reported, which include excessive tool wear for green compact electrodes, high toughness for sintered electrodes, and poor rigidity for additively manufactured electrodes. To address these issues, researchers have explored different manufacturing methods, such as casting, conventional machining, electrodeposition, powder metallurgy and additive manufacturing. In this paper, the various techniques attempted and adopted in EDM electrode manufacturing are analyzed and discussed. This paper also sought to give insight into EDM, its various forms, the dielectric fluid’s properties, EDM electrode’s size and shape, the effects of the electrode on the EDM process, material removal, electrode wear, present technologies for electrode fabrication, and the limitations of these technologies. Finally, directions for future research are highlighted. Full article

The multi-random-effects gamma process has a better characterization effect for degraded data with individual differences. In this paper, a reliability evaluation method for gamma stochastic processes with multiple random effects is studied. The mathematical model of multiple random effects gamma process was established. The model parameters estimation method was established based on the Bayesian approach. The prior distribution acquisition method was discussed, and the parameters of the multiple randomeffects gamma process were estimated by the MCMC-Gibbs method. The correctness of the model and method was verified by numerical simulation, the influence of algorithm parameters on the algorithm solving process was studied. In the fourth part, the reliability of aviation hydraulic rotary joints was studied by using multiple random effects gamma processes. Full article

Due to advantages such as a high power-to-weight ratio, a simple structure, and low cost, pneumatic systems are widely applied in automation. However, precise position control of pneumatic actuators is challenging because of factors such as friction, compressibility, and external disturbances. This paper presents a backstepping sliding mode control (BSMC) strategy based on the extended state observer (ESO) for pneumatic cylinder position tracking. A nonlinear model of the pneumatic system is first established, then system states and disturbances are estimated by an ESO, next the BSMC approach is developed using backstepping method and sliding mode control theory, and the stability of the ESO and controller is analyzed using Lyapunov theory. Finally, simulations and experiments on a pneumatic testbed are performed to compare the effectiveness of the proposed approach with PID control. The results show that the proposed strategy improves tracking accuracy and robustness against disturbances, with a 77.04% reduction in root mean square error (RMSE). This research provides a promising control solution for automated pneumatic polishing robots. Full article

Electrical losses are converted into thermal energy in motors, which heats each component. It is a significant factor in decreasing motor mechanical performance. In this paper, the motor cooling characteristics were analyzed according to the design factors of the water jacket to investigate the cooling performance of a permanent magnet synchronous motor (PMSM). First, the electrical losses generated in PMSM were calculated using electromagnetic finite element (FE) analysis. Secondly, a 3D electromagnetic–thermal fluid coupled FE analysis was performed to analyze the temperature distribution inside the motor by applying electrical loss as the heat source. Finally, the motor cooling performance according to the design factors of the water jacket was statistically analyzed using the design of experiment (DOE) method. It was found that the mass flow rate of 0.02547 kg/s and six passes of the water jacket with one inlet and two outlets could be considered the optimum conditions in terms of the maximum motor temperature. Full article

This study investigates the feasibility of utilizing a flow-induced vibration actuator as a potential energy source using piezoelectric energy harvesting. The focus is on exploring the behavior of piezo films configured as cantilever beams subjected to flow-induced vibration, which can be induced with fluid or wind streams. The primary objective is to maximize the harvested energy from the vibrating structure. This paper develops theoretical models to analyze the resonant frequencies and energy-harvesting potential of the piezo films in the context of flow-induced vibration. Experimental validations are conducted to verify the theoretical predictions. The findings indicate that higher operating frequencies in the second mode offer improved energy harvesting efficiency compared with lower modes. With the strategic adjustment of resonant frequencies using attached masses on individual piezo films, the harvestable energy output of a single film can be significantly increased from less than 1 μW to approximately 18 μW. However, the phase differences among individual piezo films can impact frequency measurements, necessitating careful fine-tuning of the physical conditions of individual components. To optimize energy harvesting, this study emphasizes the importance of implementing efficient charging mechanisms. By identifying suitable environmental vibration sources, the required charging duration for a synthesized energy harvesting array can be reduced by 25% as well. Despite certain challenges, such as phase deviations and turbulence, this study demonstrates the promising potential of flow-induced vibration resonators as sustainable energy sources. This work lays the foundation for further advancements in energy harvesting technology, offering environmentally friendly and renewable energy solutions. Full article

With the continuous increase in the capacity of the pumped storage generator motor, the overheating of the rotor area is becoming increasingly severe, which has a significant effect on the safe and reliable operation of the machine. The heat dissipation of the machine rotor by fully air-cooled is one of the key technologies to develop the new generation of pumped storage generator motors. In this paper, the electromagnetic field and fluid–thermal coupled field of a pumped storage generator motor are analyzed. The 2D transient time-step finite element model of the electromagnetic field of a pumped storage generator motor is established, and the eddy current loss of damping bars of the rotor is calculated by the finite element method. The additional loss of the rotor pole surface is calculated by analytical method. The mathematical and geometric models of the 3D fluid–thermal coupled field of the pumped storage generator motor are established and calculated. The complex fluid velocity distribution and the temperature distribution at different positions of the rotor under fully air-cooled fanless cooling conditions are investigated in detail. The calculated temperature of field winding is compared with the measured value, and the result shows that the calculated result coincident well with the test data. This research provides the technical reference for the development and temperature rise calculation for large pumped storage generator motors. Full article

The rapid evolution of electric machines requires innovative approaches to boost performance, efficiency, and sustainability. Additive Manufacturing (AM) has emerged as a transformative technique, reshaping the landscape of electric machine components, ranging from magnetic materials to windings and extending to thermal management. In the area of magnetic materials, AM’s capacity to fabricate intricate structures optimizes magnetic flux dynamics, yielding advanced shape-profile cores and self-coating laminations for superior performance. In windings, AM’s prowess is evident through innovative concepts, effectively mitigating AC conduction effects while reducing weight. Furthermore, AM revolutionizes thermal management, as exemplified by 3D-printed ceramic heat exchangers, intricate cooling channels, and novel housing designs, all contributing to enhanced thermal efficiency and power density. The integration of AM not only transcends conventional manufacturing constraints but also promises to usher in an era of unprecedented electric machine innovation, addressing the intricate interplay of magnetic, winding, and thermal dynamics. Full article

Multi-surface sliding mode control addresses the limitations of traditional sliding mode control by employing multiple sliding surfaces to handle uncertainties, disturbances, and nonlinearities. The design process involves developing sliding surfaces, designing switching logic, and deriving control laws for each surface. In this paper, first, a robust finite-time multi-surface sliding mode controller will be presented and its performance analyzed by applying it to a multirotor subjected to a suspended payload, modeled in the form of a single pendulum, itself defined as a spatial (3D) dynamic model. Next, an adaptive finite-time multi-surface sliding mode controller will be derived—adding a variable adaptive parameter to the existing sliding surfaces of the robust finite-time control—and applied to the same system. It will be shown that the adaptive controller, with an adaptive parameter that adjusts itself based on the present value of the multi-surface sliding mode parameter, creates an improved fast finite-time convergence by obtaining an optimal settling time and minimizing undershoot of the multirotor state vector. Empirical verification of the effectiveness of the adaptive control will be carried out by presenting the control performances against a step response. It is also shown that the control may be utilized to approximate external disturbances—represented by the pendulum—and that with the application of control, the vehicle’s motion may be stabilized and the payload swing suppressed. Lyapunov stability theory-based stability proofs for the controllers’ designs are developed, showing the asymptotic stability of the output and uniform boundedness of the errors in the system dynamics. It is verified that the multi-surface sliding mode control can account for system uncertainties—both matched and mismatched—in addition to changes in internal dynamics and disturbances to the system, where the single pendulum payload is representative of the changes in dynamics that may occur to the system. Numerical simulations and characteristics are presented to validate the performance of the controllers. Full article

Ergonomics is a key factor in the improvement of health and productivity in workplaces. Its use in improving the performance of a manufacturing process and its positive effects on productivity and human performance is drawing the attention of researchers and practitioners in the field of industrial engineering. This paper proposes an ergonomic design approach applied to an innovative prototype of an adaptive automation assembly system (A3S) equipped with Microsoft Kinect™ for real-time adjustment. The system acquires the anthropometric measurements of the operator by means of the 3-D sensing device and changes its layout, arranging the mobile elements accordingly. The aim of this study was to adapt the assembly workstation to the operator dimensions, improving the ergonomics of the workstation and reducing the risks of negative effects on workers’ health and safety. The case study of an assembly operation of a centrifugal electric pump is described to validate the proposed approach. The assembly operation was simulated at a traditional fixed workstation and at the A3S. The shoulder flexion angle during the assembly tasks at the A3S reduced between 18% and 47%. The ergonomic risk assessment confirmed the improvement of the ergonomic conditions and the ergonomic benefits of the A3S. Full article

The prolonged operation of machines in the production process can lead to continuous deterioration or even failure, and the necessary maintenance measures can alleviate the above negative effects. For this reason, this study investigates a joint optimization problem of single-machine production and preventive maintenance (PM) considering linear deterioration effects. The objective is to obtain an integrated sequence of degrading jobs and PM activities in order to simultaneously minimize the makespan and the total cost. Based on the problem characteristics, an adaptive PM strategy is first designed. To efficiently solve the problem, an improved multi-objective evolutionary algorithm based on decomposition (IMOEA/D) is tailored, where the biased-distribution weight vector is proposed to enhance the search capability at both ends of the Pareto front. Five instances are used to evaluate the performance of the customized IMOEA/D and two classical multi-objective evolutionary algorithms. Numerical studies show that the IMOEA/D can substantially improve the hypervolume metric, the maximum spread metric, and the distributivity of the Pareto front at a slight sacrifice of the spacing metric. Full article

Austenitic stainless steel gears were fabricated via the fine blanking process that can be used for mass production. A carbon-supersaturated (CS)-matrix high-speed steel punch was prepared to minimize the adhesive and abrasive wear damage. Its edge profile was tailored and finished to control the local metal flow around the punch edges and edge corners. This CS punch was utilized in fine blanking the AISI304 austenitic stainless steel gears. Ball-on-disc (BOD) testing was first employed to describe the frictional behavior of the CS tool steel disc against the AISI304 stainless steel balls. SEM-EDX analysis on the wear track revealed that a free-carbon tribofilm was formed in situ in the wear track to prevent adhesive wear via galling on the tool steel disc. No significant adhesive or abrasive wear was detected on the punch edges and punch edge corners after continuously fine blanking with 50 strokes. AISI304 gears were produced to have fully burnished surfaces. Their pitches, widths and circles were measured to evaluate their gear-grade balancing during the fine blanking process. The stabilized gear-grade balancing in JIS-9 to JIS-10 grades was attained for these as-blanked AISI304 gears without finishing processes. Full article

The tightening torque values considered in the assembly of vehicle subparts are of great importance in terms of connection safety. The torque value to be selected is different for each bolted joint type with respect to mechanical features. While the tightening torque value is an important indicator, the bolt preloading value is always a more reliable parameter in terms of whether a secure tightening can be achieved or not. For this reason, when it is desired to create reliable joints, the preloading value that the tightening torque input will create on the connection package should be calculated well. This study presents an integrated approach using Taguchi method (TM) and neural network (NN) to predict the self-loosening mechanism of bolted joints in automotive chassis engine suspension connections. External loading acting on the joints of the engine suspension was collected from bench tests. NN was applied to establish the relationship between controlled factors and loosening rate. The results showed that the proposed approach can be used to predict mechanism of self-loosening and behavior of bolted joints without additional tests, and it is possible to make predictions with very low error rates using artificial intelligence techniques. Full article

Kinematics is a fundamental topic in engineering, robotics, mechatronics, and control systems and significantly resolves some of these fields’ most pressing issues. It is essential to assess the balance between a topic’s theoretical framework and its empirical validation to succeed in engineering. Educational tools have gained significant attention for their ability to enhance the learning experience by providing the hands-on experiences necessary to assess theoretical frameworks and empirical validations. This paper presents a system incorporating state-of-the-art features, including a fuzzy controller enabling precise control of a linear actuator and a USB camera, to provide an interactive experience. The USB camera captures the position of the actuator, providing real-time visual feedback and allowing the students to validate their theoretical understanding through practical experiments. Precision, accuracy, resolution, and the implementation of the fuzzy controller are measured to evaluate the whole system’s performance. The design, implementation, and control of our educational electrical linear actuator for teaching kinematics concepts contribute to a practical educational tool and advance interactive learning approaches in the field. Full article

Educational mechatronics aims to be the evolution of educational robotics so it can be identified as a part of the educational paradigm of the university, its academic spaces, infrastructure, and practical activities. The fundamental goal of this framework is to develop the knowledge and skills that the new industrial world, inspired by the latest technologies, necessitates. This work proposes the modular design of a robotic arm aligned with the extended educational mechatronics conceptual framework by designing and implementing educational tools to develop the knowledge and skills required for Industry 4.0. The 3D-printed, low-cost robotic arm is designed to be used in a motion capture system for robotics applications to build kinematics concepts for a learning process. In particular, the instructional design to build the mechatronic concept of a robot workspace is carried out considering the three learning levels: concrete, representational, and abstract. The above demonstrates how the proposed pedagogical methodology can impact Industry 4.0 in the small- and medium-sized enterprises’ context. Full article

Reinforcement learning has been explored within the context of robot operation in different environments. Designing the reward function in reinforcement learning is challenging for designers because it requires specialized knowledge. To reduce the design burden, we propose a reward design method that is independent of both specific environments and tasks in which reinforcement learning robots evaluate and generate rewards autonomously based on sensor information received from the environment. This method allows the robot to operate autonomously based on sensors. However, the existing approach to adaption attempts to adapt without considering the input properties for the strength of the sensor input, which may cause a robot to learn harmful actions from the environment. In this study, we propose a method for changing the threshold of a sensor input while considering the strength of the input and other properties. We also demonstrate the utility of the proposed method by presenting the results of simulation experiments on a path-finding problem conducted in an environment with sparse rewards. Full article

Recently, applying the utilization of RGB-D data for robot perception tasks has garnered significant attention in domains like robotics and autonomous driving. However, a prominent challenge in this field lies in the substantial impact of feature robustness on both segmentation and pose estimation tasks. To tackle this challenge, we proposed a pioneering two-stage hybrid Convolutional Neural Network (CNN) architecture, which connects segmentation and pose estimation in tandem. Specifically, we developed Cross-Modal (CM) and Cross-Layer (CL) modules to exploit the complementary information from RGB and depth modalities, as well as the hierarchical features from diverse layers of the network. The CM and CL integration strategy significantly enhanced the segmentation accuracy by effectively capturing spatial and contextual information. Furthermore, we introduced the Convolutional Block Attention Module (CBAM), which dynamically recalibrated the feature maps, enabling the network to focus on informative regions and channels, thereby enhancing the overall performance of the pose estimation task. We conducted extensive experiments on benchmark datasets to evaluate the proposed method and achieved exceptional target pose estimation results, with an average accuracy of 94.5% using the ADD-S AUC metric and 97.6% of ADD-S smaller than 2 cm. These results demonstrate the superior performance of our proposed method. Full article