High-speed miniature rotary actuators are critical components in compact, high-performance systems. However, conventional electromagnetic micromotors face a prominent trade-off between miniaturization and output performance, which restricts their applicability in highly integrated devices. To address this challenge, a novel high-speed rotary piezoelectric ultrasonic motor is proposed. The proposed motor consists of a titanium alloy metal body with offset driving teeth, piezoelectric ceramic plates, two conical rotors, a compression spring, an output shaft, and a fastening sleeve. Four PZT-8 plates are bonded to the periphery of the metal body and excited to generate in-plane bending vibration modes; these vibrations are then transformed into unidirectional rotary motion through the periodic contraction and expansion of the offset driving teeth and frictional contact with the rotors. The operating principle and structural parameters of the proposed motor were analyzed and optimized using finite element analysis (FEA), including modal, harmonic response, and transient analyses. A prototype was fabricated to evaluate its mechanical properties. The stator has a compact size of 12 mm × 12 mm × 4 mm and a mass of 2.3 g. Experimental results demonstrate that under an excitation voltage of 350 Vp-p at the resonant frequency of 28.6 kHz, the motor achieves a maximum rotational speed of 4720 rpm and a maximum stall torque of 0.36 mN·m. With its simple structure, compact size, lightweight design, and excellent output performance, the proposed ultrasonic motor provides a solution for compact high-speed rotary actuation.
The Cave of Altamira (Spain), a UNESCO World Heritage site, contains one of the most fragile and inaccessible Paleolithic rock-art environments in Europe, where geomatics documentation is constrained not only by severe spatial, lighting and safety limitations but also by conservation-driven restrictions on time, access and operational procedures. This study applies a confined-space UAV equipped with LiDAR-based SLAM navigation to document and assess the stability of the vertical rock wall leading to “La Hoya” Hall, a structurally sensitive sector of the cave. Twelve autonomous and assisted flights were conducted, generating dense LiDAR point clouds and video sequences processed through videogrammetry to produce high-resolution 3D meshes. A Mask R-CNN deep learning model was trained on manually segmented images to explore automated crack detection under variable illumination and viewing conditions. The results reveal active fractures, overhanging blocks and sediment accumulations located on inaccessible ledges, demonstrating the capacity of UAV-SLAM workflows to overcome the limitations of traditional surveys in confined subterranean environments. All datasets were integrated into the DiGHER digital twin platform, enabling traceable storage, multitemporal comparison, and collaborative annotation. Overall, the study demonstrates the feasibility of combining UAV-based SLAM mapping, videogrammetry and deep learning segmentation as a reproducible baseline workflow to inform preventive conservation and future multitemporal monitoring in Paleolithic caves and similarly constrained cultural heritage contexts.
Understanding how the brain integrates motor suppression with motivational processes remains a fundamental question in neuroscience. The rostral Pedunculopontine nucleus, a brainstem structure involved in motor control, has been shown to induce transient motor arrest upon optogenetic or electrical stimulation. However, our current understanding of its potential role in linking motor suppression with motivational or reinforcement-related processes is still insufficient. To further explore the effects induced by PPN stimulations and infer the potential mechanism underlying its role involved in both motor and emotional regulation, we developed a fully automated, low-cost system combining real-time animal tracking with closed-loop optogenetic stimulation, using the OpenMV Cam H7 Plus and embedded neural network models. The system autonomously detects the rat's position and triggers optical stimulation upon entry into a predefined region of interest, enabling unbiased, unsupervised behavioral assays. Optogenetic activation of CaMKIIa-expressing neurons in the rostral PPN reliably induced transient motor arrest. When motor arrest was spatially paired with a defined region of interest, rats developed a robust place preference after limited training. These results suggest that rostral PPN activation can couple motor inhibition with reinforcement-related behavioral circuitry. Together, our work provides both a technical framework for scalable closed-loop neuroscience experiments and preliminary evidence that the rostral PPN may participate in coordinating motor suppression with motivational processes.
Jan Ulrich Bartels, Alexander Achberger, Katherine J. Kuchenbecker
et al.
We describe the hardware design, force-rendering approach, and evaluation of a new reconfigurable haptic interface consisting of a network of hybrid motor-brake actuation modules that apply forces via cables. Each module contains both a motor and a brake, enabling it to smoothly render active forces up to 6 N using its motor and collision forces up to 186 N using its passive one-way brake. The modular design, meanwhile, allows the system to deliver rich haptic feedback in a flexible number of DoF and widely ranging configurations.
Currently, research on the rotational modulation of dual-axis inertial navigation for isolated carrier motion does not provide sufficient solutions for the compensation of the gyroscope scale factor error caused by the Earth’s rotation. Moreover, it is primarily applied to ships with low maneuverability and has not yet been implemented in the field of pure inertial guidance weapons. A dual-axis inertial isolation rotation modulation method is proposed to address this issue, taking into account the application characteristics of long-endurance guided weapons. An analysis of the system error characteristics under the coupling of multiple error sources acting on IMU was conducted, and it was found that the angular velocity of the inertial isolation carrier can significantly reduce the output error of the IMU. A dual-axis inertial isolation shaft system installation error compensation algorithm was designed, and an improvement was made based on the traditional sixteen-sequence rotation scheme to compensate for the projection components of the Earth’s rotation and carrier motion on the inner and outer frame rotation axes, achieving the inertial isolation rotation modulation function of dual-axis inertial navigation. Based on the attitude changes in long-range guided weapons, Monte Carlo simulation verification was conducted, and the results showed that this scheme can improve inertial navigation accuracy by 10% to 20%.
Kinetics of biological motors such as kinesin or dynein is notably influenced by viscoelastic intracellular environment. The characteristic relaxation time of the cytosol is not separable from the colloidal timescale and therefore their dynamics is inherently non-Markovian. In this paper we consider a variant of a Brownian motor model, namely a Brownian ratchet immersed in a correlated thermal bath and analyze how memory influences its dynamics. In particular, we demonstrate the memory-induced current reversal effect and explain this phenomenon by applying the effective mass approximation as well as uncovering the memory-induced dynamical localization of the motor trajectories in the phase space. Our results reveal new aspects of the role of memory in microscopic systems out of thermal equilibrium.
Automotive telemetry data exhibits slow drifts and fast spikes, often within the same sequence, making reliable anomaly detection challenging. Standard reconstruction-based methods, including sequence variational autoencoders (VAEs), use a single latent process and therefore mix heterogeneous time scales, which can smooth out spikes or inflate variances and weaken anomaly separation. In this paper, we present STREAM-VAE, a variational autoencoder for anomaly detection in automotive telemetry time-series data. Our model uses a dual-path encoder to separate slow drift and fast spike signal dynamics, and a decoder that represents transient deviations separately from the normal operating pattern. STREAM-VAE is designed for deployment, producing stable anomaly scores across operating modes for both in-vehicle monitors and backend fleet analytics. Experiments on an automotive telemetry dataset and the public SMD benchmark show that explicitly separating drift and spike dynamics improves robustness compared to strong forecasting, attention, graph, and VAE baselines.
The development of unmanned aerial vehicles (UAVs) has attracted much attention in the global community and aviation industry. As UAVs have the potential to be applied for multiple missions, the level of research into improving their design and flight performance has also increased. In this context, the present paper aims to present the design, construction, and flight performance of an electrically operated fixed-wing UAV. As a first step in the design process, key performance requirements are defined, such as the thrust required, the stall speed, the minimum drag velocity, and the minimum power velocity. Wing and associated power loadings are calculated according to the defined performance requirements. In addition, payload and endurance requirements are set up in order to determine the wing and tail areas, the total mass, the power requirements, and the motor size. Aerodynamics and stability designs are also calculated. After the completion of the design process, the manufacturing of the UAV follows by using appropriate materials. Flight tests were carried out for the evaluation of the UAV’s flight performance, where the success of the design was demonstrated.
In the marine environment, the motion characteristics of Autonomous Underwater Vehicles (AUVs) are influenced by unknown factors such as time-varying ocean currents, thereby amplifying the complexity involved in the design of path-following controllers. In this study, a backstepping sliding mode control method based on a current observer and nonlinear disturbance observer (NDO) has been developed, addressing the 3D path-following issue for AUVs operating in the ocean environment. Accounting for uncertainties like variable ocean currents, this research establishes the AUV’s kinematics and dynamics models and formulates the tracking error within the Frenet–Serret coordinate system. The kinematic controller is designed through the line-of-sight method and the backstepping method, and the dynamic controller is developed using the nonlinear disturbance observer and the integral sliding mode control method. Furthermore, an ocean current observer is developed for the real-time estimation of current velocities, thereby mitigating the effects of ocean currents on navigational performance. Theoretical analysis confirms the system’s asymptotic stability, while numerical simulation attests to the proposed method’s efficacy and robustness in 3D path following.
Mihai-Vladut HOTHAZIE, Ionut BUNESCU, Mihaita-Gilbert STOICAN
et al.
The present study highlights the benefits of using vortex generators as a passive boundary layer control method to delay the flow separation. Using high fidelity CFD analysis, a parametric study regarding the optimum position of vortex generators is carried out using an in-house automation procedure. After that, relevant quantities such as wall shear stress, turbulent kinetic energy, pressure coefficient distribution and oil flow visualization are analyzed and corresponding conclusions are drawn. The use of turbulent and energy quantities allows to quantify the impact of the generated vortices on the boundary layer and to identify the optimal positioning of vortex generators for improved aerodynamic performance.
Localized tooth breakage is one of the common failures of spur gears, which affects the smooth and safe operation of spur gear transmission systems. The tooth collision cannot be neglected, and it is especially important to reveal the meshing-impacting dynamic characteristics of the gear system under localized tooth breakage to improve the safe and stable operation of the gear system. Based on the gear meshing principle and the dissipative collision contact force model, the drive-side tooth meshing model and back-side tooth impacting model are established with considering the transient nature of tooth back-side contact. The tooth surface meshing model and tooth back collision model under partial breakage are established. According to the contact state and force environment of the gear pair, the multi-state meshing-impacting behaviour under local breakage is classified, and the discrete meshing-impact dynamics model of an involute spur gear system under local breakage is established to explore the influence of local breakage on the meshing stiffness and load distribution. The mechanism of contact force under partial tooth breakage is revealed, and the influence of load coefficient and meshing frequency on the nonlinear dynamics is studied by defining two Poincaré maps. It is found that local tooth breakage affects the contact force of single-and double-tooth meshes and reduces gear load carrying capacity. Larger loads inhibit back-side impact, and smaller loads induce the coexistence behaviour and back-side impact. Larger or smaller meshing frequency induce back-side impact behaviour. The coexistence of chaotic and periodic motions induces back-side impact behaviour, and localized tooth breakage affects the coexistence phenomenon and aggravates the complexity of the dynamic behaviour. The dynamic model of gear system considering energy dissipation and nonlinear vibration under the presence of local tooth breakage of the pinion is explored, and the conditions of back-side impact are studied. This research provides new methods and ideas for nonlinear dynamic modelling and analysis of faulty gear systems.
The article is devoted to the issue of evaluating the piloting performance of an aircraft, taking into account various factors that have a special effect on the control process. The article presents the results of work on the creation of models of a digital indicator on the windshield and the power circuit of the hydraulic system and consumers in the longitudinal control channel of the aircraft for conducting research in the field of assessing their impact on piloting accuracy when the aircraft moves along an assigned flight path during landing. The features of the process of developing the elements of the indicator on the windshield, namely the indicators of the director ring and the velocity vector, their control law when the aircraft moves along an assigned flight path are presented. The implementation of the effect of the hinge moment on the steering actuators in the model of the hydraulic system of the aircraft when the stabilizer consoles deviate from a neutral angular position is described. The principle of integration of a Simulink model of a hydraulic system and a flash model of a windshield indicator with a model of spatial motion of a heavy aircraft is presented. The results of semi-natural simulation on a flight simulator are presented, on the basis of which the values of deviations from a given flight path are calculated when performing a turn in a circle, the mode in which the hinge moment limits the angle of deviation of the stabilizer consoles is determined. It is concluded that it is advisable to create and use an experimental base to provide research in the field of assessing the impact of promising information sources that provide flight information to the crew in poor weather conditions, and the operation of the hydraulic system on the aircraft piloting performance and the pilot’s control actions in various flight modes of the aircraft.
We have used numerical simulations to investigate how the properties of motor proteins control the dynamical behavior of a driven flexible filament. The filament is pinned at one end and positioned on top of a patch of anchored motor proteins, a setup commonly referred to as a spiral gliding assay. In nature, there is a variety of motor proteins with different properties. In this study, we have investigated the role of detachment rate, detachment force, stall force, and unloaded speed of motors on the dynamical behavior of the filament. We found that this system generally can show three different regimes: 1) Fluctuation, where the filament undergoes random fluctuations because the motors are unable to bend it. 2) Rotation, in which the filament bends and then moves continuously in one direction. 3) Beating, where the filament's direction of rotation changes over time. We found that the transition between fluctuation and rotation occurs when motors exert a force sufficient to buckle the filament. The threshold force coincides to the second buckling mode of a filament undergoing a continuously distributed load. Moreover, we showed that when motors near the pining point work close to their stall force, they get stuck and act as a second pin, leading to the beating regime.
Asher Winter, Navid Mohajer, Darius Nahavandi
et al.
Human Centrifuge Systems (HCSs) are an effective training tool to improve the G-acceleration and Spatial Disorientation (SD) tolerance of aircrew. Though highly capable HCSs are available, their structure and performance are yet to be fully optimised to efficiently recreate the G-vectors produced using Aircraft Combat Manoeuvres (ACMs). To achieve this improvement, the relationship between configurational design and HCS performance should be profoundly investigated. This work proposes a framework for identifying the optimal configurational design of an active four Degree-of-Freedom (DoF) HCS. The relationship between configurational design parameters and objective criteria is established using inverse kinematics and dynamics. Then, a multi-objective evolutionary optimiser is used to identify the optimum arm length and seat position, minimising the Coriolis effect, relative acceleration ratio, and cost. The results of the work show that the applied optimisation step can significantly contribute to (1) efficiently replicating the aircraft motion, (2) minimising the detrimental effects generated during HCS motion, and (3) reducing the overall cost of the system. The applied methodology can be adapted to HCSs with different structures and DoFs.
Motor imagery (MI) is a well-documented technique used by subjects in BCI (Brain Computer Interface) experiments to modulate brain activity within the motor cortex and surrounding areas of the brain. In our term project, we conducted an experiment in which the subjects were instructed to perform motor imagery that would be divided into two classes (Right and Left). Experiments were conducted with two different types of electrodes (Gel and POLiTag) and data for individual subjects was collected. In this paper, we will apply different machine learning (ML) methods to create a decoder based on offline training data that uses evidence accumulation to predict a subject's intent from their modulated brain signals in real-time.
Marco P. M. de Souza, Sidnei P. Oliveira, Valdenice L. Luiz
In this work, we present the Electric Motor simulator, an application on the SimuFísica platform intended for use in the classroom. We briefly describe the technologies behind the application, the equations that govern its operation, some studies showing the dynamics of the electric motor and, finally, examples of approach in the classroom. -- Apresentamos neste trabalho o simulador Motor elétrico, um aplicativo da plataforma SimuFísica voltado para uso em sala de aula. Descrevemos brevemente as tecnologias por trás do aplicativo, as equações que regem o seu funcionamento, alguns estudos mostrando a dinâmica do motor elétrico e, por fim, exemplos de abordagem em sala de aula.
Thomas Klotz, Lena Lehmann, Francesco Negro
et al.
Objective: Studying motor units (MUs) is essential for understanding motor control, the detection of neuromuscular disorders and the control of human-machine interfaces. Individual motor unit firings are currently identified in vivo by decomposing electromyographic (EMG) signals. Due to our body's properties and anatomy, individual motor units can only be separated to a limited extent with surface EMG. Unlike electrical signals, magnetic fields do not interact with human tissues. This physical property and the emerging technology of quantum sensors make magnetomyography (MMG) a highly promising methodology. However, the full potential of MMG to study neuromuscular physiology has not yet been explored. Approach: In this work, we perform in silico trials that combine a biophysical model of EMG and MMG with state-of-the-art algorithms for the decomposition of motor units. This allows the prediction of an upper-bound for the motor unit decomposition accuracy. Main results: It is shown that non-invasive high-density MMG data is superior over comparable high-density surface EMG data for the robust identification of the discharge patterns of individual motor units. Decomposing MMG instead of EMG increased the number of identifiable motor units by 76%. Notably, MMG exhibits a less pronounced bias to detect superficial motor units. Significance: The presented simulations provide insights into methods to study the neuromuscular system non-invasively and in vivo that would not be easily feasible by other means. Hence, this study provides guidance for the development of novel biomedical technologies.
In order to obtain the influence of water entry angle and speed on the cavitation and impact load characteristics of supercavitating vehicle, a high-speed water entry numerical model of supercavitating vehicle based on VOF model is established, and the accuracy of the model is verified by relative experiments. Through simulation, the cavitation evolution process, cavitation size, impact load change and surface pressure distribution of supercavitating vehicle entering water at different angles and velocities are obtained and compared. The results show that with the increase of water entry velocity, the depth of cavitation closing position increases, the cavitation size increases, the peak value of axial load increases and the surface pressure of vehicle increases; With the increase of water entry angle, the bubble closing time remains unchanged, the bubble size decreases, the axial load peak increases, and the asymmetry of pressure distribution decreases. The pressure on the upstream surface of the cavitator increases along the radius to the center of the circle, but the asymmetry decreases when it enters the water obliquely.
Missions targeting the extreme and rugged environments on the moon and Mars have rich potential for a high science return, although several risks exist in performing these exploration missions. The current generation of robots is unable to access these high-priority targets. We propose using teams of small hopping and rolling robots called SphereX that are several kilograms in mass and can be carried by a large rover or lander and tactically deployed for exploring these extreme environments. Considering that the importance of minimizing the mass and volume of these robot platforms translates into significant mission-cost savings, we focus on the optimization of an integrated power and propulsion system for SphereX. Hydrogen is used as fuel for its high energy, and it is stored in the form of lithium hydride and oxygen in the form of lithium perchlorate. The system design undergoes optimization using Genetic Algorithms integrated with gradient-based search techniques to find optimal solutions for a mission. Our power and propulsion system, as we show in this paper, is enabling, because the robots can travel long distances to perform science exploration by accessing targets not possible with conventional systems. Our work includes finding the optimal mass and volume of SphereX, such that it can meet end-to-end mission requirements.