Search Results (3,341)

The origin of life initiated an evolutionary continuum yielding biologically optimized systems capable of operating under extreme environmental constraints. Biomimetics, defined as the systematic abstraction and transfer of biological principles into engineering domains, has become a strategic design paradigm for addressing the multifactorial challenges of space systems. This study introduces two core contributions to formally establish the discipline of Aerospace Bionic Robotics (ABR): First, it elucidates the relevance of biologically derived functionalities such as autonomy, adaptability, and multifunctionality to enhance the efficiency of space robotic platforms operating in microgravity environments. Second, it proposed the BEAM-D (Biomimetic Engineering and Aerospace Mechatronics Design), a standard for the development of Aerospace Bionic Robotics. By integrating biological abstraction levels (morphological, functional, and behavioral) with engineering protocols including ISO, VDI, and NASA’s TRL, BEAM-D enables a structured design pathway encompassing subsystem specification, cyber–physical integration, in situ testing, and full-scale mission deployment. It is implemented through a modular BEAM-DX framework and reinforced by iterative BIOX design steps. This study thus establishes formalized bio-inspired design tools for advanced orbital and planetary robotic systems capable of sustained autonomous operations in deep space exploration scenarios. Full article

Conductive hydrogels (CHs) have attracted significant attention in the fields of flexible electronics, human–machine interaction, and electronic skin (e-skin) due to their self-adhesiveness, environmental stability, and multi-stimuli responsiveness. However, integrating these diverse functionalities into a single conductive hydrogel system remains a challenge. In this study, polyvinyl alcohol (PVA) and polyacrylamide (PAM) were used as the dual-network matrix, lithium chloride and MXene were added, and a simple immersion strategy was adopted to synthesize a multifunctional MXene-based conductive hydrogel in a glycerol/water (1:1) binary solvent system. A subsequent investigation was then conducted on the hydrogel. The prepared PVA/PAM/LiCl/MXene hydrogel exhibits excellent tensile properties (~1700%), high electrical conductivity (1.6 S/m), and good self-healing ability. Furthermore, it possesses multimodal sensing performance, including humidity sensitivity (sensitivity of −1.09/% RH), temperature responsiveness (heating sensitivity of 2.2 and cooling sensitivity of 1.5), and fast pressure response/recovery times (220 ms/230 ms). In addition, the hydrogel has successfully achieved real-time monitoring of human joint movements (elbow and knee bending) and physiological signals (pulse, breathing), as well as enabled monitoring of spatial pressure distribution via a 3 × 3 sensor array. The performance and versatility of this hydrogel make it a promising candidate for next-generation flexible sensors, which can be applied in the fields of human health monitoring, electronic skin, and human–machine interaction. Full article

Humidity sensing elements based on sodium-doped titanium dioxide (Na-doped TiO₂) were prepared using a sol–gel method in the presence of cerium ions and sintered at 400 °C and 800 °C. Titanium (IV) n-butoxide and a saturated solution of diammonium hexanitratocerate in isobutanol served as starting materials. Sodium hydroxide and sodium tert-butoxide were used as inorganic and organometallic sodium sources, respectively. The influence of sodium additives on the properties of the humidity sensing elements was systematically investigated. The surface morphologies of the obtained layers were examined by scanning electron microscopy (SEM). Elemental mapping was conducted by energy-dispersive X-ray (EDX) spectroscopy, and structural characterization was performed using X-ray diffractometry (XRD). Electrical properties were studied for samples sintered at different temperatures over a relative humidity range of 15% to 95% at 20 Hz and 25 °C. Experimental results indicate that sodium doping enhances humidity sensitivity compared to undoped reference samples. Incorporation of sodium additives increases the resistance variation range of the sensing elements, reaching over five orders of magnitude for samples sintered at 400 °C and four orders of magnitude for those sintered at 800 °C. Full article

Hydrogen bonding, a prevalent molecular interaction in nature, is crucial in biological and chemical processes. The emergence of single-molecule techniques has enhanced our microscopic understanding of hydrogen bonding. However, it is still challenging to track the dynamic behaviour of hydrogen bonding in solution, particularly under physiological conditions where interactions are significantly weakened. Here, we present a nanoscale-confined, functionalised quantum mechanical tunnelling (QMT) probe that enables continuous monitoring of electrical fingerprints of single-molecule hydrogen bonding interactions for over tens of minutes in diverse solvents, including polar physiological solutions, which reveal reproducible multi-level conductance distributions. Moreover, the functionalised QMT probes have successfully discriminated between L(+)- and D(−)-tartaric acid enantiomers by resolving the conductance difference. This work uncovers dynamic single-molecule hydrogen bonding processes within confined nanoscale spaces under physiological conditions, establishing a new paradigm for probing molecular hydrogen-bonding networks in supramolecular chemistry and biology. Full article

Pilot visual behavior safety assessment is a cross-disciplinary technology that analyzes pilots’ gaze behavior and neurocognitive responses. This paper proposes a multimodal analysis method for pilot visual behavior safety, specifically for cognitive state decoding. This method aims to achieve a quantitative and efficient assessment of pilots’ observational behavior. Addressing the subjective limitations of traditional methods, this paper proposes an observational behavior detection model that integrates facial images to achieve dynamic and quantitative analysis of observational behavior. It addresses the “Midas contact” problem of observational behavior by constructing a cognitive analysis method using multimodal signals. We propose a bidirectional long short-term memory (LSTM) network that matches physiological signal rhythmic features to address the problem of isolated features in multidimensional signals. This method captures the dynamic correlations between multiple physiological behaviors, such as prefrontal theta and chest-abdominal coordination, to decode the cognitive state of pilots’ observational behavior. Finally, the paper uses a decision-level fusion method based on an improved Dempster–Shafer (DS) evidence theory to provide a quantifiable detection strategy for aviation safety standards. This dual-dimensional quantitative assessment system of “visual behavior–neurophysiological cognition” reveals the dynamic correlations between visual behavior and cognitive state among pilots of varying experience. This method can provide a new paradigm for pilot neuroergonomics training and early warning of vestibular-visual integration disorders. Full article

In the research and development system of bat-like flapping-wing flying robots, lift modeling and numerical analysis are the key theoretical basis, which will directly affect the construction of the body structure and flight control system. However, due to the complex three-dimensional flapping motion mechanism of bats and the flexible deformation characteristics of their wing membranes, the existing lift theory lacks a mature calculation method suitable for bionic flapping-wing flying robots. In this paper, the wing membrane deformation mechanism of a bat-like flapping-wing flying robot is studied, and the coupling effect of wing membrane motion and deformation on flight parameters is analyzed. A set of calculation methods for flexible morphing wing membrane lift is improved by using a quasi-steady model and the blade element method. By comparing and analyzing the theoretical calculation and experimental results under various working conditions, the error is less than 4%, which proves the effectiveness of this method. Full article

As stroke is becoming more frequent nowadays, cutting edge rehabilitation approaches are required to recover upper limb functionalities and to support patients during daily activities. Recently, focus has moved to robotic rehabilitation; however, therapeutic devices are still highly expensive, making rehabilitation not easily affordable. Moreover, devices are not easily accepted by patients, who can refuse to use them due to not feeling comfortable. The presented work proposes the exploitation of a virtual prototype of the human–robot ecosystem for the study and analysis of patient–robot interactions, enabling their simulation-based investigation in multiple scenarios. For the accomplishment of this task, the Dynamics of Multi-physical Systems platform, previously presented by the authors, is further developed to enable the integration of biomechanical models of the human body with mechatronics models of robotic devices for motion assistance, as well as with PID-based control strategies. The work begins with (1) a description of the background; hence, the current state of the art and purpose of the study; (2) the platform is then presented and the system is formalized, first from a general side and then (3) in the application-specific scenario. (4) The use case is described, presenting a controlled gym weightlifting exercise supported by an exoskeleton and the results are analyzed in a final paragraph (5). Full article

In this study, a vision-based remote and synchronized control scheme is proposed for the double six-DOF robotic manipulators. Using an Intel RealSense D435 depth camera and MediaPipe skeletal image feature technique, the operator’s 3D hand pose is captured and mapped to the robot’s workspace via coordinate transformation. Inverse kinematics is then applied to compute the necessary joint angles for synchronized motion control. Implemented on double robotic manipulators with the MoveIt framework, the system successfully achieves a collaborative teleoperation control task to transfer an object from a robotic manipulator to another one. Further, moving average filtering techniques are used to enhance trajectory smoothness and stability. The framework demonstrates the feasibility and effectiveness of non-contact, vision-guided multi-robot control for applications in teleoperation, smart manufacturing, and education. Full article

Microfluidic methods are powerful platforms for synthesizing advanced functional materials because they allow for precise control of microscale reaction environments. Microfluidics manipulates reactants in lab-on-a-chip systems to enable the fabrication of highly uniform materials with tunable properties, which are crucial for drug delivery, diagnostics, catalysis, and nanomaterial design. This review emphasizes recent progress in microfluidic technologies for synthesizing functional materials, with a focus on polymeric, hydrogel, lipid-based, and inorganic particles. Microfluidics provides exceptional control over the size, morphology, composition, and surface chemistry of materials, thereby enhancing their performance through uniformity, tunability, hierarchical structuring, and on-chip functionalization. Our review provides novel insights by linking material design strategies with fabrication methods tailored to biomedical applications. We also discuss emerging trends, such as AI-driven optimization, automation, and sustainable microfluidic practices, offering a practical and forward-looking perspective. As the field advances toward robust, standardized, and user-friendly platforms, microfluidics has the potential to increase industrial adoption and enable on-demand solutions in nanotechnology and personalized medicine. Full article

CFRP is extensively utilized in the manufacturing of aerospace equipment owing to its distinctive properties, and hole-making processing continues to be the predominant processing method for this material. However, due to the anisotropy of CFRP, in its processing process, processing damage appears easily, such as stratification, fiber tearing, burrs, etc. These damages will seriously affect the performance of CFRP components in the service process. This work employs acoustic emission (AE) and infrared thermography (IT) techniques to analyze the characteristics of AE signals and temperature signals generated during the CFRP drilling process. Fast Fourier transform (FFT) and short-time Fourier transform (STFT) are used to process the collected AE signals. And in combination with the actual damage morphology, the material removal behavior during the drilling process and the AE signal characteristics corresponding to processing defects are studied. The results show that the time-frequency graph and root mean square (RMS) curve of the AE signal can accurately distinguish the different stages of the drilling process. Through the analysis of the frequency domain characteristics of the AE signal, the specific frequency range of the damage mode of the CFRP composite material during drilling is determined. This paper aims to demonstrate the feasibility of real-time monitoring of the drilling process. By analyzing the relationship between the RMS values of acoustic emission signals and hole surface topography under different drilling parameters, it provides a new approach for the research on online monitoring of CFRP drilling damage and improvement of CFRP machining quality. Full article

Object detection in soccer scenes serves as a fundamental task for soccer video analysis and target tracking. This paper proposes WCC-YOLO, a symmetry-enhanced object detection framework based on YOLOv11n. Our approach integrates symmetry principles at multiple levels: (1) The novel C3k2-WTConv module synergistically combines conventional convolution with wavelet decomposition, leveraging the orthogonal symmetry of Haar wavelet quadrature mirror filters (QMFs) to achieve balanced frequency-domain decomposition and enhance multi-scale feature representation. (2) The Channel Prior Convolutional Attention (CPCA) mechanism incorporates symmetrical operations—using average-max pooling pairs in channel attention and multi-scale convolutional kernels in spatial attention—to automatically learn to prioritize semantically salient regions through channel-wise feature recalibration, thereby enabling balanced feature representation. Coupled with InnerShape-IoU for refined bounding box regression, WCC-YOLO achieves a 4.5% improvement in mAP@0.5:0.95 and a 5.7% gain in mAP@0.5 compared to the baseline YOLOv11n while simultaneously reducing the number of parameters and maintaining near-identical inference latency (δ < 0.1 ms). This work demonstrates the value of explicit symmetry-aware modeling for sports analytics. Full article

The excellent mechanical properties of AISI 201 make it well-suited for applications in industrial components, transportation, and household appliances. However, during machining, this material generates high cutting forces and temperatures, leading to rapid tool wear and high costs. To address this issue, micro-grooves were designed on the rake face in areas prone to thermal and mechanical stress concentration. Through machining experiments focusing on workpiece surface quality, it was found that micro-grooved tools produced superior surface quality, specifically manifested in lower surface roughness, reduced work hardening, and shallower hardened layer depth. Experiments demonstrate that under identical conditions, increasing the cutting speed with tool M reduces the workpiece surface roughness by 0.096 μm to 0.236 μm compared to tool O. Under identical conditions, increasing the feed rate with tool M reduces the workpiece surface roughness by 0.070 μm to 0.236 μm compared to tool O. As cutting speed varies, the absolute surface hardness of workpieces machined by tool M decreases by approximately 39.85 HV, representing a hardness reduction of 14.5%. As feed rate varies, the surface hardness of workpieces machined with tool M is suppressed to a level 10.2%–14.2% lower than that of tool O. As cutting depth varies, the surface hardness of workpieces machined with tool M is suppressed to a level 10.0%–14.7% lower than that of tool O. Additionally, micro-grooved tools demonstrated superior chip curling and breaking performance. This tool design approach, optimized for tool durability and workpiece surface quality, establishes a research foundation for tool design targeting difficult-to-machine materials. Full article

There is a strong coupling between two arms in cooperative operations of dual-arm robots. To enhance the coordination and cooperation ability of dual-arm robots, a force-closure-based weighted hybrid force/position fuzzy coordination control method is proposed. Firstly, to improve the grasping stability of dual-arm robots, the force-closure dynamic constraints are established by combining the friction cone constraints with the force and torque balance constraints. Then the optimal distribution of contact force is performed according to the minimum energy consumption principle. Secondly, to enhance the coordination of dual-arm robots, the weighted hybrid force/position control method is modified by adding the synchronization error between two arms. Then the Lyapunov method is adopted to prove the stability of the proposed coordination control method. Thirdly, the fuzzy self-tuning technique is adopted to adjust the control gains automatically. Lastly, a simulation and experiment are performed for collaborative transport. The results show that, compared with the position coordination control and the traditional hybrid force/position control, the weighted hybrid force/position fuzzy coordination control can improve control accuracy and has good cooperation ability and strong robustness. Therefore, the proposed method can effectively realize the coordination control of dual-arm robots. Full article

Recent research has focused on energy recovery and storage technologies. One of the materials allowing the recovery of dissipated energy is the piezoelectric material (PE). These functional materials perform reversible energy conversion, transforming electrical energy into mechanical and vice versa. In this study, we investigate the recovery of vibratory energy in vehicle suspension systems—energy traditionally dissipated by conventional shock absorbers—using piezoelectric materials to capture this wasted energy and redirect it to the vehicle’s auxiliary power supply network. We propose an integrated electromechanical model incorporating piezoelectric actuators in parallel with the suspension mechanism. The collected energy is processed and stored for later use in powering accessories such as windows and mirrors. The idea is to integrate renewable energy sources to optimize the performance of the vehicle. We proposed a Multiphysics model of the system under a software used to this type of modeling (Simcenter AMESim v1610_student). The simulation results of the system and its various sub-systems are presented for studying the piezo-actuator response to reduce consumption and increase energy performance in a vehicle. These findings will undergo experimental validation in the project’s subsequent phase. Full article

The enhancement of drug delivery into the lung surfactant is facilitated by research on the interaction between drugs and the lung surfactant. Drug designers must have a thorough theoretical understanding of a drug before performing clinical tests to reduce the experimental cost. The current study uses a coarse-grained molecular dynamics (MD) approach with the MARTINI force field to parameterize the corticosteroid drug mometasone furoate, which is used to treat lung inflammation. Here, we investigate the accurate parametrization of drug molecules and validate the parameters with the help of umbrella sampling simulations. A collection of thermodynamic parameters was studied during the parametrization procedure. The Gibbs free energy gradient was used to calculate the partition coefficient value of mometasone furoate, which was approximately 10.49 based on our umbrella sampling simulation. The value was then matched with the experimental and predicted the partition coefficient of the drug, showing good agreement. The drug molecule was then delivered into the lung surfactant monolayer membrane at the alveolar air–water interface, resulting a concentration-dependent drop in surface tension while controlling the underlying continual compression–expansion of alveoli that maintains the exhalation–inhalation respiratory cycle. The dynamical properties of the monolayer demonstrate that the drug’s capacity to diffuse into the monolayer is considerably diminished in larger clusters, and this effect is intensified when there are more drug molecules present in the monolayer. The monolayer microstructure analysis shows that the drug concentration controls monolayer morphology. The results of this investigation may be helpful for corticosteroid drug delivery into the lung alveoli, which can be applied to comprehend how the drug interacts with lung surfactant monolayers or bilayers. Full article