Abstracts:Traditional quadcopters excel in flight agility and maneuverability, but often face limitations in hovering efficiency and horizontal field of view. Nature-inspired rotary wings, while offering a broader perspective and enhanced hovering efficiency, are hampered by substantial angular momentum restrictions. In this study, we introduce QuadRotary, a novel vehicle that integrates the strengths of both flight characteristics through a reconfigurable design. With no additional actuators and featuring innovative designs, such as magnet-assisted hinges and self-folding wings, QuadRotary is able to achieve bidirectional in-flight transitions. Our evaluation of the prototype, control law, and transition strategies through various flight experiments demonstrates QuadRotary's capability for agile cruising and hovering, maintaining stabilized yaw rates ranging from 0 to 45 rad/s. Notably, the recorded power consumption highlights an approximately 18.4% increase in hovering efficiency with rotary-wing configuration, attributed to the presence of wings. These findings not only underscore QuadRotary's superior operational and tasking efficiency compared to existing applications but also suggest other potential implementations in the future.

Abstracts:This article proposes a practical actuator-level loop-shaping control method that enables stable position and attitude control of quadrotors undergoing continuous, high-rate yaw motion for omnidirectional perception. To this end, we first identify and formalize the key control challenges arising from high yaw rates. Accordingly, the proposed scheme is developed to compensate for the gyroscopic coupling, reject disturbances through integral control action, and accelerate actuator response via an extended-state-observer-based tracking differentiator that provides a feed-forward torque derivative. In addition to its control capabilities, the modular and lightweight design offers flexibility for integration with high-level position and attitude controllers and ensures low computational overhead for real-time onboard implementation. Real-flight experiments validate the proposed approach, demonstrating stable hovering and trajectory tracking at yaw rates up to 5.5 Hz—the fastest reported to date—while operating on a 480-MHz microcontroller with a computation time of only 3 $\mathrm{\mu }\mathrm{s}$ per cycle.

Abstracts:A centrifugal dynamic visualization test system was designed to analyze the dynamic response process and microscopic contact state of MEMS inertial switches under centrifugal load. An optical test system is used to visualize the inertial switches on their axis of rotation, enabling the device's response to be observed. In particular, this article uses the variable mass method to rapidly and efficiently analyze the sequential motion mechanism of inertial switches by using the test system. The results demonstrate that the test system can visualize the sequential motion process of inertial switches under centrifugal action. The test system can be used to observe and record the motion in an area of less than 100 μm × 100 μm more clearly at high rotational speeds. It substantiates the assertion that the test system effectively observes the working mechanism of devices under centrifugal action.

Abstracts:Heavy-duty operations, typically performed using heavy-duty hydraulic manipulators (HHMs), are susceptible to environmental contact due to tracking errors or sudden environmental changes. Therefore, in addition to precise control, it is essential for the manipulator to maintain stability and reduce the risk of damage to both itself and the environment during contact, without relying on contact-force sensors, which are typically impractical for these applications. This article proposes a novel force-sensorless robust impact-resilient controller for a generic 6-degree-of-freedom (DoF) HHM constituting from anthropomorphic arm and spherical wrist mechanisms. The scheme consists of a neuroadaptive subsystem-based impedance controller, which is designed to ensure both accurate tracking of position and orientation with stabilization of HHMs upon contact, along with a novel generalized momentum observer, which is for the first time introduced in Plücker coordinate, to estimate the impact force. Finally, by leveraging the concepts of virtual stability and virtual power flow, the semiglobal uniformly ultimately boundedness of the entire system is assured. Extensive experiments and simulation comparisons conducted on a generic 6-DoF industrial HHM validate the method's exceptional performance in achieving subcentimeter accuracy for desired trajectory tracking. Furthermore, the results demonstrate that equipping the controller with impact-resiliency features reduces the impact force from unintended contacts by 80% .

Abstracts:The increased flexibility and introduced coupling between links and cylinders pose challenges for modeling flexible hydraulic manipulators (FHMs). The traditional assumed mode method (AMM) encounters the problems of low computational accuracy resulting from a single basis function, as well as the low computational efficiency of multidegree-of-freedom calculations. In this article, a novel dynamic modeling method utilizing Lagrange’s dynamic equation with a multibasis function combination is proposed. To increase the modeling accuracy, flexible deflections are determined through a linear combination of several basis functions. All these basis functions are derived using the Rayleigh–Ritz method by considering geometric deformation boundary conditions and curvature changes in the links. To improve computational efficiency, the flexible link system is divided into two virtual rigid and flexible parts, which are analyzed separately to minimize the impact of coupling terms. Deflections in the dynamic equation affect only the flexible eigenmatrix and its derivative term such that the dynamic equations are simplified. The experiments on a 13-m FHM verify that, compared with the traditional AMM, the proposed modeling method can effectively increase accuracy while improving computational efficiency.

Abstracts:Deep neural networks (DNNs) have shown excellent performance in fault diagnosis, but this heavily relies on training datasets with high-quality labels. However, both manual annotation and automatic annotators inevitably introduce noisy labels into the dataset, which mislead the model during training and negatively affect generalization, especially in strong noisy environments. Therefore, this article proposes a multigranularity label construction approach via multigranularity cluster fusion (MgCF), aiming to more efficiently suppress the misleading effect of noisy labels. MgCF first constructs a granular cluster for each sample in the latent feature space based on the estimation of the noise intensity of the training dataset, and estimates the membership relationship of the sample to each category based on the distribution of labels in the cluster. Then, by fusing the membership relationship with the original observation label, a corrected multigranularity label is obtained. Finally, the fusion label replaces the original label to complete the training process. A series of experimental results and theoretical analyses confirm MgCF's effectiveness, offering a robust training strategy for intelligent fault diagnosis even with low-quality, cost-effective datasets. MgCF has the potential to expand the practical application of such datasets, advancing the development of intelligent mechatronic systems.

Abstracts:The lack of 3-D localization impedes the advancement of various intracorporeal medical devices. Developing an occlusion-free, small-sized, and high-precision positioning system remains a significant challenge in the practical application of interventional robotics. In this article, a novel 5-degree of freedom (DoF) positioning system utilizing single-axis electromagnetic field excitation coil is designed to locate a microcoil with a size of $\phi$ 1.45 × 5 mm. An XGBoost-based induced electromotive force (EMF) prediction model is proposed to correct the deviation of the magnetic dipole model near the excitation source. Employing the model, a positioning dataset under rotating magnetic field is synthesized. Subsequently, a CNN-LSTM based 5-DoF positioning model is designed and trained, and the transmitting coil speed characteristics of the model were experimentally verified. Evaluation experiments for the two models are performed separately. The results demonstrate the XGBoost-based EMF prediction model improved the prediction accuracy by 34.4% compared to the conventional magnetic dipole model. The static average localization error of the 5-DoF positioning model is 2.53 mm and the orientation error is 2.24$^\circ$ within the $\phi$ 150 × 70 mm volume. The dynamic tracking experimental results indicate that the localization tracking error is 4.25 mm and the orientation error is 3.44$^\circ$, which are 62% and 78% higher than the Levenberg–Marquardt algorithm. The navigation experiment conducted in a coronary artery phantom demonstrated the potential for use in narrow tracts.

Abstracts:Joint stiffness control is essential for safe and compliant human–robot interaction in rehabilitation exoskeletons. Variable stiffness actuators (VSAs), with controllable physical stiffness, offers a potential solution. However, existing VSAs generally do not allow both motors to contribute to power output simultaneously, which limits their performance in human–robot interaction. Therefore, the goal of this article is to develop a novel variable stiffness actuator with dual-motor load sharing (DMLS-VSA) and its stiffness and torque control scheme. The innovative DMLS-VSA mechanism features a power transmission mechanism (PTM) and a variable stiffness mechanism (VSM). The PTM enables the DMLS-VSA to have dual-motor load sharing capability, allowing the output power to be determined by both motors. Meanwhile, the VSM utilizes a modified planetary gear mechanism to achieve stiffness variation by regulating the effective lever arm length. In this differential configuration, the motion of both motors changes the output torque and stiffness. Consequently, a novel cascade PI controller, with the position-loop control term acting directly on the deflection angle and stiffness, is used to control the DMLS-VSA, preventing undesired movements during motion. The performance of the DMLS-VSA is verified through experiments on stiffness regulation, torque control, physical human–robot interaction, and the dual-motor load sharing capability, demonstrating its suitability for rehabilitation exoskeleton applications.

Abstracts:The function of proportional electromagnet is to proportionally convert the electrical signal into a mechanical quantity, the output axial electromagnetic force is proportional to the input current or voltage within the effective stroke of the armature. Because there is a radial gap between the armature and the guide sleeve, the armature is prone to be eccentric with the guide sleeve, and a unbalanced radial electromagnetic force is generated. The guide sleeve bears the radial pressure of the armature, and then generates friction that hinders the movement of the armature, which decreased sensitivity and linearity of the proportional electromagnet. The eccentricity problem of the armature and the guide sleeve is put forward in this article, the causes and hazards of unbalanced radial electromagnetic force are analyzed, the calculation formula of the unbalanced radial electromagnetic force is deduced, and simulation calculations and experimental research are conducted. The results reveal that the unbalanced radial electromagnetic force acting on the armature is approximately proportional to the eccentricity, and increases with the decrease of the axial working air gap between the armature and the basin-shaped pole piece, and rapidly raises with the increase of the coil current. To reduce the unbalanced radial electromagnetic force, a spline type armature is designed, which significantly reduces the eccentricity and unbalanced radial electromagnetic force, simultaneously reduces the contact area and motion resistance of the precise clearance between the armature and the guide sleeve, hence improves the sensitivity and linearity of the proportional electromagnet.

Abstracts:Variational mode decomposition (VMD) is a signal processing technique used to analyze bearing faults by breaking down signals into simpler components. While effective, traditional VMD requires users to manually set key parameters—such as the initial center frequency $\omega ^{1}$, the penalty parameter $\alpha$, and the number of modes $K$—which, if improperly selected, can obscure fault features or reduce analytical clarity. To overcome these limitations, we propose a parametric self-contained VMD (PSVMD) method. Specifically, $\omega ^{1}$ is automatically determined based on the narrowband features of the signal, removing the need for manual selection. Furthermore, adaptive strategies are introduced to estimate both $\alpha$ and $K$ based on the intrinsic properties of the decomposed modes, thereby enhancing accuracy and robustness. Building on PSVMD, we also propose a novel correlation-kurtosis index to effectively distinguish fault-related features from noise. Simulation results and real-world bearing fault data validate the effectiveness and superiority of the proposed method.