Many processes may be used for manufacturing functionally graded materials. Among them, additive manufacturing seems to be predestined due to near-net shape manufacturing of complex geometries combined with the possibility of applying different materials in one component. By adjusting the powder composition of the starting material layer by layer, a macroscopic and step-like gradient can be achieved. To further improve the step-like gradient, an enhancement of the in-situ mixing degree, which is limited according to the state of the art, is necessary. In this paper, a novel technique for an enhancement of the in-situ material mixing degree in the melt pool by applying laser remelting (LR) is described. The effect of layer-wise LR on the formation of the interface was investigated using pure copper and low-alloy steel in a laser powder bed fusion process. Subsequent cross-sectional selective electron microscopic analyses were carried out. By applying LR, the mixing degree was enhanced, and the reaction zone thickness between the materials was increased. Moreover, an additional copper and iron-based phase was formed in the interface, resulting in a smoother gradient of the chemical composition than the case without LR. The Marangoni convection flow and thermal diffusion are the driving forces for the observed effect.
In recent years, the robot industry has developed rapidly, and researchers and enterprises have begun to pay more attention to this industry. People are barely familiar with climbing robots, a kind of special robot. However, from their practical value and scientific research value, climbing robots should studied further. This paper analyzes and summarizes the key technologies of climbing robots, introduces various kinds of climbing robots, and examines their advantages and disadvantages to provide a reference for future researchers. Many countries have studied climbing robots and made some achievements. However, due to the complexity of climbing robots, their climbing efficiency and accuracy need to be further improved. The new structure can improve the climbing efficiency. This paper analyzes climbing robots such as mechanical arms, magnetic attraction, and claws. Optimization methods and path planning can improve the accuracy of work. This paper involves some control methods, including complex intelligent control methods such as behavior-based robot control. This paper also investigates various kinematic planning methods and expounds and summarizes various path planning algorithms, including machine learning and reinforcement learning of artificial intelligence, ant colony algorithm, and other algorithms. Therefore, by analyzing the research status of climbing robots at home and abroad, this paper summarizes three important aspects of climbing robots, namely, structural design, control methods, and climbing strategies, elaborates on the achievements and existing problems of these key technologies, and looks forward to the future development trend and research direction of climbing robots.
The noncontact blade tip timing (BTT) measurement has been an attractive technology for blade health monitoring (BHM). However, the severe undersampled BTT signal causes a significant challenge for blade vibration parameter identification and fault feature extraction. This study proposes a novel method based on the minimum variance distortionless response (MVDR) of the direction of arrival (DoA) estimation for blade natural frequency estimation from the non-uniformly undersampled BTT signals. First, based on the similarity between the general data acquisition model for BTT and the antenna array model in DoA estimation, the circumferentially arranged probes on the casing can be regarded as a non-uniform linear array. Thus, BTT signal reconstruction is converted into the DoA estimation problem of the non-uniform linear array signal. Second, MVDR is employed to address the severe undersampling issue and recover the BTT undersampled signal. In particular, spatial smoothing is innovatively utilized to enhance the estimation of covariance matrix of the BTT signal to avoid ill-condition or singularity, while improving efficiency and robustness. Lastly, numerical simulation and experimental testing are employed to verify the validity of the proposed method. Monte Carlo simulation results suggest that the proposed method behaves better than conventional methods, especially under a lower signal-to-noise ratio condition. Experimental results indicate that the proposed method can effectively overcome the severe undersampling problem of BTT signal induced by physical limitations, and has a strong potential in the field of BHM.
The smart toolholder is the core component in the development of intelligent and precise manufacturing. It enables in situ monitoring of cutting data and machining accuracy evolution and has become a focal point in academic research and industrial applications. However, current table and rotational dynamometers for milling force, vibration, and temperature testing suffer from cumbersome installation and provide only a single acquisition signal, which limits their use in laboratory settings. In this study, we propose a wireless smart toolholder with multi-sensor fusion for simultaneous sensing of milling force, vibration, and temperature signals. We select force, vibration, and temperature sensors suitable for smart toolholder fusion to adapt to the cutting environment. Thereafter, structural design, circular runout, dynamic balancing, static stiffness, and dynamic inherent frequency tests are conducted to assess its dynamic and static performance. Finally, the smart toolholder is tested for accuracy and repeatability in terms of force, vibration, and temperature. Experimental results demonstrate that the smart toolholder accurately captures machining data with a relative deviation of less than 1.5% compared with existing force gauges and provides high repeatability of milling temperature and vibration signals. Therefore, it is a smart solution for machining condition monitoring.
Compacted graphite iron (CGI) is considered to be an ideal diesel engine material with excellent physical and mechanical properties, which meet the requirements of energy conservation and emission reduction. However, knowledge of the microstructure evolution of CGI and its impact on flow stress remains limited. In this study, a new modeling approach for the stress–strain relationship is proposed by considering the strain hardening effect and stored energy caused by the microstructure evolution of CGI. The effects of strain, strain rate, and deformation temperature on the microstructure of CGI during compression deformation are examined, including the evolution of graphite morphology and the microstructure of the pearlite matrix. The roundness and fractal dimension of graphite particles under different deformation conditions are measured. Combined with finite element simulation models, the influence of graphite particles on the flow stress of CGI is determined. The distributions of grain boundary and geometrically necessary dislocations (GNDs) density in the pearlite matrix of CGI under different strains, strain rates, and deformation temperatures are analyzed by electron backscatter diffraction technology, and the stored energy under each deformation condition is calculated. Results show that the proportion and amount of low-angle grain boundaries and the average GNDs density increase with the increase of strain and strain rate and decreased first and then increased with an increase in deformation temperature. The increase in strain and strain rate and the decrease in deformation temperature contribute to the accumulation of stored energy, which show similar variation trends to those of GNDs density. The parameters in the stress–strain relationship model are solved according to the stored energy under different deformation conditions. The consistency between the predicted results from the proposed stress–strain relationship and the experimental results shows that the evolution of stored energy can accurately predict the stress–strain relationship of CGI.
Given the limited operating ability of a single robotic arm, dual-arm collaborative operations have become increasingly prominent. Compared with the electrically driven dual-arm manipulator, due to the unknown heavy load, difficulty in measuring contact forces, and control complexity during the closed-chain object transportation task, the hydraulic dual-arm manipulator (HDM) faces more difficulty in accurately tracking the desired motion trajectory, which may cause object deformation or even breakage. To overcome this problem, a compliance motion control method is proposed in this paper for the HDM. The mass parameter of the unknown object is obtained by using an adaptive method based on velocity error. Due to the difficulty in obtaining the actual internal force of the object, the pressure signal from the pressure sensor of the hydraulic system is used to estimate the contact force at the end-effector (EE) of two hydraulic manipulators (HMs). Further, the estimated contact force is used to calculate the actual internal force on the object. Then, a compliance motion controller is designed for HDM closed-chain collaboration. The position and internal force errors of the object are reduced by the feedback of the position, velocity, and internal force errors of the object to achieve the effect of the compliance motion of the HDM, i.e., to reduce the motion error and internal force of the object. The required velocity and force at the EE of the two HMs, including the position and internal force errors of the object, are inputted into separate position controllers. In addition, the position controllers of the two individual HMs are designed to enable precise motion control by using the virtual decomposition control method. Finally, comparative experiments are carried out on a hydraulic dual-arm test bench. The proposed method is validated by the experimental results, which demonstrate improved object position accuracy and reduced internal force.
Edge preparation can remove cutting edge defects, such as burrs, chippings, and grinding marks, generated in the grinding process and improve the cutting performance and service life of tools. Various edge preparation methods have been proposed for different tool matrix materials, geometries, and application requirements. This study presents a scientific and systematic review of the development of tool edge preparation technology and provides ideas for its future development. First, typical edge characterization methods, which associate the microgeometric characteristics of the cutting edge with cutting performance, are briefly introduced. Then, edge preparation methods for cutting tools, in which materials at the cutting edge area are removed to decrease defects and obtain a suitable microgeometry of the cutting edge for machining, are discussed. New edge preparation methods are explored on the basis of existing processing technologies, and the principles, advantages, and limitations of these methods are systematically summarized and analyzed. Edge preparation methods are classified into two categories: mechanical processing methods and nontraditional processing methods. These methods are compared from the aspects of edge consistency, surface quality, efficiency, processing difficulty, machining cost, and general availability. In this manner, a more intuitive understanding of the characteristics can be gained. Finally, the future development direction of tool edge preparation technology is prospected.
The internal force antagonism (IFA) problem is one of the most important issues limiting the applications and popularization of redundant parallel robots in industry. Redundant cable-driven parallel robots (RCDPRs) and redundant rigid parallel robots (RRPRs) behave very differently in this problem. To clarify the essence of IFA, this study first analyzes the causes and influencing factors of IFA. Next, an evaluation index for IFA is proposed, and its calculating algorithm is developed. Then, three graphical analysis methods based on this index are proposed. Finally, the performance of RCDPRs and RRPRs in IFA under three configurations are analyzed. Results show that RRPRs produce IFA in nearly all the areas of the workspace, whereas RCDPRs produce IFA in only some areas of the workspace, and the IFA in RCDPRs is milder than that RRPRs. Thus, RCDPRs more fault-tolerant and easier to control and thus more conducive for industrial application and popularization than RRPRs. Furthermore, the proposed analysis methods can be used for the configuration optimization design of RCDPRs.
Soft arms have shown great application potential because of their flexibility and compliance in unstructured environments. However, soft arms made from soft materials exhibit limited cargo-loading capacity, which restricts their ability to manipulate objects. In this research, a novel soft arm was developed by coupling a rigid origami exoskeleton with soft airbags. The joint module of the soft arm was composed of a deployable origami exoskeleton and three soft airbags. The motion and load performance of the soft arm of the eight-joint module was tested. The developed soft arm withstood at least 5 kg of load during extension, contraction, and bending motions; exhibited bistable characteristics in both fully contracted and fully extended states; and achieved a bending angle of more than 240° and a contraction ratio of more than 300%. In addition, the high extension, contraction, bending, and torsional stiffnesses of the soft arm were experimentally demonstrated. A kinematic-based trajectory planning of the soft arm was performed to evaluate its error in repetitive motion. This work will provide new design ideas and methods for flexible manipulation applications of soft arms.
Nanoparticle-enhanced coolants (NPECs) are increasingly used in minimum quantity lubrication (MQL) machining as a green lubricant to replace conventional cutting fluids to meet the urgent need for carbon emissions and achieve sustainable manufacturing. However, the thermophysical properties of NPEC during processing remain unclear, making it difficult to provide precise guidance and selection principles for industrial applications. Therefore, this paper reviews the action mechanism, processing properties, and future development directions of NPEC. First, the laws of influence of nano-enhanced phases and base fluids on the processing performance are revealed, and the dispersion stabilization mechanism of NPEC in the preparation process is elaborated. Then, the unique molecular structure and physical properties of NPECs are combined to elucidate their unique mechanisms of heat transfer, penetration, and anti-friction effects. Furthermore, the effect of NPECs is investigated on the basis of their excellent lubricating and cooling properties by comprehensively and quantitatively evaluating the material removal characteristics during machining in turning, milling, and grinding applications. Results showed that turning of Ti‒6Al‒4V with multi-walled carbon nanotube NPECs with a volume fraction of 0.2% resulted in a 34% reduction in tool wear, an average decrease in cutting force of 28%, and a 7% decrease in surface roughness Ra, compared with the conventional flood process. Finally, research gaps and future directions for further applications of NPECs in the industry are presented.
Passive vibration isolation systems have been widely applied due to their low power consumption and high reliability. Nevertheless, the design of vibration isolators is usually limited by the narrow space of installation, and the requirement of heavy loads needs the high supporting stiffness that leads to the narrow isolation frequency band. To improve the vibration isolation performance of passive isolation systems for dynamic loaded equipment, a novel modular quasi-zero stiffness vibration isolator (MQZS-VI) with high linearity and integrated fluid damping is proposed. The MQZS-VI can achieve high-performance vibration isolation under a constraint mounted space, which is realized by highly integrating a novel combined magnetic negative stiffness mechanism into a damping structure: The stator magnets are integrated into the cylinder block, and the moving magnets providing negative-stiffness force also function as the piston supplying damping force simultaneously. An analytical model of the novel MQZS-VI is established and verified first. The effects of geometric parameters on the characteristics of negative stiffness and damping are then elucidated in detail based on the analytical model, and the design procedure is proposed to provide guidelines for the performance optimization of the MQZS-VI. Finally, static and dynamic experiments are conducted on the prototype. The experimental results demonstrate the proposed analytical model can be effectively utilized in the optimal design of the MQZS-VI, and the optimized MQZS-VI broadened greatly the isolation frequency band and suppressed the resonance peak simultaneously, which presented a substantial potential for application in vibration isolation for dynamic loaded equipment.
This study proposes a B-spline-based multiresolution and multimaterial topology optimization (TO) design method for fail-safe structures (FSSs), aiming to achieve efficient and lightweight structural design while ensuring safety and facilitating the postprocessing of topological structures. The approach involves constructing a multimaterial interpolation model based on an ordered solid isotropic material with penalization (ordered-SIMP) that incorporates fail-safe considerations. To reduce the computational burden of finite element analysis, we adopt a much coarser analysis mesh and finer density mesh to discretize the design domain, in which the density field is described by the B-spline function. The B-spline can efficiently and accurately convert optimized FSSs into computer-aided design models. The 2D and 3D numerical examples demonstrate the significantly enhanced computational efficiency of the proposed method compared with the traditional SIMP approach, and the multimaterial TO provides a superior structural design scheme for FSSs. Furthermore, the postprocessing procedures are significantly streamlined.
3D printing is a versatile technology capable of rapidly fabricating intricate geometric structures and enhancing the performance of flexible devices in comparison to conventional fabrication methods. However, 3D-printed devices are susceptible to failure as a result of minuscule structural impairments, thereby impacting their overall durability. The utilization of self-healing, biodegradable materials in 3D printing holds immense potential for increasing the longevity and safety of devices, thereby expanding the application prospects for such devices. Nevertheless, enhancing the self-repairing capability of devices and refining the 3D printing performance of self-healing materials are still considerable challenges that need to be addressed to achieve optimal outcomes. This paper reviews recent developments in the field of advancements in 3D printing using self-healing and biodegradable materials. First, it investigates self-healing and biodegradable materials that are compatible with 3D printing techniques, discussing their printability, material properties, and factors that influence print quality. Then, it explores practical applications of self-healing and biodegradable 3D printing technology in depth. Finally, it critically offers practical perspectives on this topic.
Piezoelectric actuators are a class of actuators that precisely transfer input electric energy into displacement, force, or movement outputs efficiently via inverse piezoelectric effect-based electromechanical coupling. Various types of piezoelectric actuators have sprung up and gained widespread use in various applications in terms of compelling attributes, such as high precision, flexibility of stoke, immunity to electromagnetic interference, and structural scalability. This paper systematically reviews the piezoelectric materials, operating principles, representative schemes, characteristics, and potential applications of each mainstream type of piezoelectric actuator. Herein, we intend to provide a more scientific and nuanced perspective to classify piezoelectric actuators into direct and indirect categories with several subcategories. In addition, this review outlines the pros and cons and the future development trends for all kinds of piezoelectric actuators by exploring the relations and mechanisms behind them. The rich content and detailed comparison can help build an in-depth and holistic understanding of piezoelectric actuators and pave the way for future research and the selection of practical applications.
Owing to their excellent performance and large design space, curvilinear fiber-reinforced composite structures have gained considerable attention in engineering fields such as aerospace and automobile. In addition to the stiffness and strength of such structures, their stability also needs to be taken into account in the design. This study proposes a level-set-based optimization framework for maximizing the buckling load of curvilinear fiber-reinforced composite structures. In the proposed method, the contours of the level set function are used to represent fiber paths. For a composite laminate with a certain number of layers, one level set function is defined by radial basis functions and expansion coefficients for each layer. Furthermore, the fiber angle at an arbitrary point is the tangent orientation of the contour through this point. In the finite element of buckling, the stiffness and geometry matrices of an element are related to the fiber angle at the element centroid. This study considers the parallelism constraint for fiber paths. With the sensitivity calculation of the objective and constraint functions, the method of moving asymptotes is utilized to iteratively update all the expansion coefficients regarded as design variables. Two numerical examples under different boundary conditions are given to validate the proposed approach. Results show that the optimized curved fiber paths tend to be parallel and equidistant regardless of whether the composite laminates contain holes or not. Meanwhile, the buckling resistance of the final design is significantly improved.
The planetary roller screw mechanism (PRSM) is a novel precision transmission mechanism that realizes the conversion between linear and rotary motions. The contact characteristics of helical surfaces directly determine PRSM’s performance in load-carrying capacity and transmission accuracy. Therefore, studying the contact characteristics of PRSM forms the fundamental basis for enhancing its transmission performance. In this study, a three-dimensional parametric analysis method of contact characteristics is proposed based on the PRSM meshing principle and PyVista (a high-level API to the Visualization Toolkit). The proposed method considers the influence of machining errors among various thread teeth. The effects of key machining errors on contact positions and axial clearance, as well as their sensitivities, are analyzed. With excellent solution accuracy, this method exhibits higher calculation efficiency and stronger robustness than the analytical and numerical meshing models. The influence of nominal diameter and pitch errors of the screw, roller, and nut on the axial clearance follows a linear relationship, whereas flank angle errors have negligible effects on the axial clearance. The corresponding influence coefficients for these three machining errors on the axial clearance are 0.623, 0.341, and 0.036. The variations in contact positions caused by individual errors are axisymmetric. Flank angle errors and roller diameter errors result in linear displacements of the contact points, whereas pitch errors cause the contact points to move along the arc of the roller diameter. Based on the proposed three-dimensional parametric contact characteristics analysis method, the Fuzzy C-Means clustering algorithm considering error sensitivity is utilized to establish a component grouping technique in the selective assembly of critical PRSM components, ensuring the rational and consistent clearances based on the given component’s machining errors. This study provides effective guidance for analyzing contact characteristics and grouping in selective assembly for PRSM components. It also presents the proposed method’s potential applicability to similar calculation problems for contact positions and clearances in other transmission systems.
Achieving dynamic compliance for energy-efficient legged robot motion is a longstanding challenge. Although recent predictive control methods based on single-rigid-body models can generate dynamic motion, they all assume infinite energy, making them unsuitable for prolonged robot operation. Addressing this issue necessitates a mechanical structure with energy storage and a dynamic control strategy that incorporates feedback to ensure stability. This work draws inspiration from the efficiency of bio-inspired muscle–tendon networks and proposes a controllable torsion spring leg structure. The design integrates a spring-loaded inverted pendulum model and adopts feedback delays and yield springs to enhance the delay effects. A leg control model that incorporates motor loads is developed to validate the response and dynamic performance of a leg with elastic joints. This model provides torque to the knee joint, effectively reducing the robot’s energy consumption through active or passive control strategies. The benefits of the proposed approach in agile maneuvering of quadruped robot legs in a realistic scenario are demonstrated to validate the dynamic motion performance of the leg with elastic joints with the advantage of energy-efficient legs.
Robots with transformable tracked mechanisms are widely used in complex terrains because of their high adaptability, and many studies on novel locomotion mechanisms have been conducted to make them able to climb higher obstacles. Developing underactuated transformable mechanisms for tracked robots could decrease the number of actuators used while maintaining the flexibility and obstacle-crossing capability of these robots, and increasing their cost performance. Therefore, the underactuated tracked robots have appreciable research potential. In this paper, a novel tracked robot with a newly proposed underactuated revolute‒revolute‒prismatic (RRP) transformable mechanism, which is inspired by the sit-up actions of humans, was developed. The newly proposed tracked robot has only two actuators installed on the track pulleys for moving and does not need extra actuators for transformations. Instead, it could concentrate the track belt’s tension toward one side, and the unbalanced tension would drive the linkage mechanisms to change its configuration. Through this method, the proposed underactuated design could change its external shape to create support points with the terrain and move its center of mass actively at the same time while climbing obstacles or crossing other kinds of terrains, thus greatly improving the climbing capability of the robot. The geometry and kinematic relationships of the robot and the crossing strategies for three kinds of typical obstacles are discussed. On the basis of such crossing motions, the parameters of links in the robot are designed to make sure the robot has sufficient stability while climbing obstacles. Terrain-crossing dynamic simulations were run and analyzed to prove the feasibility of the robot. A prototype was built and tested. Experiments show that the proposed robot could climb platforms with heights up to 33.3% of the robot’s length or cross gaps with widths up to 43.5% of the robot’s length.
The planned missions to explore the surfaces of the Moon and Mars require high exploration efficiency, thus imposing new demands on the mobility system of planetary rovers. In this paper, a design method for a high-speed planetary rover (HPR) is proposed, and the representative configurations are modeled and simulated. First, the influence of the planetary surface environment on the design of HPRs is analyzed, and the design factors for HPRs are determined by studying a single-wheel suspension. Second, a design methodology for HPRs is proposed. The adaptive suspension mechanisms of a four-wheeled rover are synthesized using the all-wheel-attachment condition and position and orientation characteristics theory, which are expressed in the form of a graph theory for the increase in elastic components and active joints. Finally, a dynamic model is built, and a simulation is carried out for the proposed rover. The validity of the proposed method and rover is verified, thus highlighting their potential application in future planetary exploration.
Robots are playing an increasingly important role in engineering applications. Soft robots have promising applications in several fields due to their inherent advantages of compliance, low density, and soft interactions. A soft gripper based on bio-inspiration is proposed in this study. We analyze the cushioning and energy absorption mechanism of human fingertips in detail and provide insights for designing a soft gripper with a variable stiffness structure. We investigate the grasping modes through a large deformation modeling approach, which is verified through experiments. The characteristics of the three grasping modes are quantified through testing and can provide guidance for robotics manipulation. First, the adaptability of the soft gripper is verified by grasping multi-scale and extremely soft objects. Second, a cushioning model of the soft gripper is proposed, and the effectiveness of cushioning is verified by grasping extremely sharp objects and living organisms. Notably, we validate the advantages of the variable stiffness of the soft gripper, and the results show that the soft robot can robustly complete assemblies with a gap of only 0.1 mm. Owing to the unstructured nature of the engineering environment, the soft gripper can be applied in complex environments based on the abovementioned experimental analysis. Finally, we design the soft robotics system with feedback capture based on the inspiration of human catching behavior. The feasibility of engineering applications is initially verified through fast capture experiments on moving objects. The design concept of this robot can provide new insights for bionic machinery.
Small tracking error correction for electro-optical systems is essential to improve the tracking precision of future mechanical and defense technology. Aerial threats, such as “low, slow, and small (LSS)” moving targets, pose increasing challenges to society. The core goal of this work is to address the issues, such as small tracking error correction and aiming control, of electro-optical detection systems by using mechatronics drive modeling, composite velocity–image stability control, and improved interpolation filter design. A tracking controller delay prediction method for moving targets is proposed based on the Euler transformation model of a two-axis, two-gimbal cantilever beam coaxial configuration. Small tracking error formation is analyzed in detail to reveal the scientific mechanism of composite control between the tracking controller’s feedback and the motor’s velocity–stability loop. An improved segmental interpolation filtering algorithm is established by combining line of sight (LOS) position correction and multivariable typical tracking fault diagnosis. Then, a platform with 2 degrees of freedom is used to test the system. An LSS moving target shooting object with a tracking distance of S = 100 m, target board area of A = 1 m2, and target linear velocity of v = 5 m/s is simulated. Results show that the optimal method’s distribution probability of the tracking error in a circle with a radius of 1 mrad is 66.7%, and that of the traditional method is 41.6%. Compared with the LOS shooting accuracy of the traditional method, the LOS shooting accuracy of the optimized method is improved by 37.6%.
The efficient dynamic modeling and vibration transfer analysis of a fluid-delivering branch pipeline (FDBP) are essential for analyzing vibration coupling effects and implementing vibration reduction optimization. Therefore, this study proposes a reduced-order dynamic modeling method suitable for FDBPs and then analyzes the vibration transfer characteristics. For the modeling method, the finite element method and absorbing transfer matrix method (ATMM) are integrated, considering the fluid–structure coupling effect and fluid disturbances. The dual-domain dynamic substructure method is developed to perform the reduced-order modeling of FDBP, and ATMM is adopted to reduce the matrix order when solving fluid disturbances. Furthermore, the modeling method is validated by experiments on an H-shaped branch pipeline. Finally, transient and steady-state vibration transfer analyses of FDBP are performed, and the effects of branch locations on natural characteristics and vibration transfer behavior are analyzed. Results show that transient vibration transfer represents the transfer and conversion of the kinematic, strain, and damping energies, while steady-state vibration transfer characteristics are related to the vibration mode. In addition, multiple-order mode exchanges are triggered when branch locations vary in frequency-shift regions, and the mode-exchange regions are also the transformation ones for vibration transfer patterns.
With the continued shrinking of the critical dimensions (CDs) of wafer patterning, the requirements for modeling precision in optical proximity correction (OPC) increase accordingly. This requirement extends beyond CD controlling accuracy to include pattern alignment accuracy because misalignment can lead to considerable overlay and metal-via coverage issues at advanced nodes, affecting process window and yield. This paper proposes an efficient OPC modeling approach that prioritizes pattern-shift-related elements to tackle the issue accurately. Our method integrates careful measurement selection, the implementation of pattern-shift-aware structures in design, and the manipulation of the cost function during model tuning to establish a robust model. Confirmatory experiments are performed on a via layer fabricated using a negative tone development. Results demonstrate that pattern shifts can be constrained within a range of ±1 nm, remarkably better than the original range of ±3 nm. Furthermore, simulations reveal notable differences between post OPC and original masks when considering pattern shifts at locations sensitive to this phenomenon. Experimental validation confirms the accuracy of the proposed modeling approach, and a firm consistency is observed between the simulation results and experimental data obtained from actual design structures.
A key challenge is using bionic mechanisms to enhance aerodynamic performance of hover-capable flapping wing micro air vehicle (FWMAV). This paper presented a new lift system with high lift and aerodynamic efficiency, which use a hummingbird as a bionic object. This new lift system is able to effectively utilize the high lift mechanism of hummingbirds, and this study innovatively utilizes elastic energy storage elements and installs them at the wing root to help improve aerodynamic performance. A flapping angle of 154° is achieved through the optimization of the flapping mechanism parameters. An optimized wing shape and parameters are obtained through experimental studies on the wings. Consequently, the max net lift generated is 17.6% of the flapping wing vehicle’s weight. Moreover, energy is stored and released periodically during the flapping cycle, by imitating the musculoskeletal system at the wing roots of hummingbirds, thereby improving the energy utilization rate of the FWMAV and reducing power consumption by 4.5% under the same lift. Moreover, strength verification and modal analyses are conducted on the flapping mechanism, and the weight of the flapping mechanism is reduced through the analysis and testing of different materials. The results show that the lift system can generate a stable lift of 31.98 g with a wingspan of 175 mm, while the lift system weighs only 10.5 g, providing aerodynamic conditions suitable for high maneuverability flight of FWMAVs.
The dynamic motion of quadrupedal robots on challenging terrain generally requires elaborate spatial–temporal kinodynamic motion planning and accurate control at higher refresh rate in comparison with regular terrain. However, conventional quadrupedal robots usually generate relatively coarse planning and employ motion replanning or reactive strategies to handle terrain irregularities. The resultant complex and computation-intensive controller may lead to nonoptimal motions or the breaking of locomotion rhythm. In this paper, a kinodynamic optimization approach is presented. To generate long-horizon optimal predictions of the kinematic and dynamic behavior of the quadruped robot on challenging terrain, we formulate motion planning as an optimization problem; jointly treat the foot’s locations, contact forces, and torso motions as decision variables; combine smooth motion and minimal energy consumption as the objective function; and explicitly represent feasible foothold region and friction constraints based on terrain information. To track the generated motions accurately and stably, we employ a whole-body controller to compute reference position and velocity commands, which are fed forward to joint controllers of the robot’s legs. We verify the effectiveness of the developed approach through simulation and on a physical quadruped robot testbed. Results show that the quadruped robot can successfully traverse a 30° slope and 43% of nominal leg length high step while maintaining the rhythm of dynamic trot gait.
Manufacturing flexible magnetic-driven actuators with complex structures and magnetic arrangements to achieve diverse functionalities is becoming a popular trend. Among various manufacturing technologies, magnetic-assisted digital light processing (DLP) stands out because it enables precise manufacturing of macro-scale structures and micro-scale distributions with the assistance of an external magnetic field. Current research on manufacturing magnetic flexible actuators mostly employs single materials, which limits the magnetic driving performance to some extent. Based on these characterizations, we propose a multi-material magnetic field-assisted DLP technology to produce flexible actuators with an accuracy of 200 μm. The flexible actuators are printed using two materials with different mechanical and magnetic properties. Considering the interface connectivity of multi-material printing, the effect of interfaces on mechanical properties is also explored. Experimental results indicate good chemical affinity between the two materials we selected. The overlap or connection length of the interface moderately improves the tensile strength of multi-material structures. In addition, we investigate the influence of the volume fraction of the magnetic part on deformation. Simulation and experimental results indicate that increasing the volume ratio (20% to 50%) of the magnetic structure can enhance the responsiveness of the actuator (more than 50%). Finally, we successfully manufacture two multi-material flexible actuators with specific magnetic arrangements: a multi-legged crawling robot and a flexible gripper capable of crawling and grasping actions. These results confirm that this method will pave the way for further research on the precise fabrication of magnetic flexible actuators with diverse functionalities.
The concept of remote center of motion (RCM) is pivotal in a myriad of robotic applications, encompassing areas such as medical robotics, orientation devices, and exoskeletal systems. The efficacy of RCM technology is a determining factor in the success of these robotic domains. This paper offers an exhaustive review of RCM technologies, elaborating on their various methodologies and practical implementations. It delves into the unique characteristics of RCM across different degrees of freedom (DOFs), aiming to distill their fundamental principles. In addition, this paper categorizes RCM approaches into two primary classifications: design based and control based. These are further organized according to their respective DOFs, providing a concise summary of their core methodologies. Building upon the understanding of RCM’s versatile capabilities, this paper then transitions to an in-depth exploration of its applications across diverse robotic fields. Concluding this review, we critically analyze the existing research challenges and issues that are inherently present in both RCM methodologies and their applications. This discussion is intended to serve as a guiding framework for future research endeavors and practical deployments in related areas.
Natural mechanical materials, such as bamboo and bone, often exhibit superior specific mechanical properties due to their hierarchical porous architectures. Using the principle of hierarchy as inspiration can facilitate the development of hierarchical mechanical metamaterials (HMMs) across multiple length scales via 3D printing. In this work, we propose self-similar HMMs that combine octet-truss (OCT) architecture as the first and second orders, with cubic architecture as the third or more orders. These HMMs were fabricated using stereolithography 3D printing, with the length sizes ranging from approximately 200 µm to the centimeter scale. The compressive stress–strain behaviors of HMMs exhibit a zigzag characteristic, and the toughness and energy absorption can be significantly enhanced by the hierarchical architecture. The compressive moduli are comparable to that of natural materials, and the strengths are superior to that of most polymer/metal foams, alumina hollow/carbon lattices, and other natural materials. Furthermore, the flexural stress–strain curves exhibit a nonlinear behavior, which can be attributed to the hierarchical architecture and local damage propagation. The relatively high mechanical properties can be attributed to the synergistic effect of the stretch-dominated OCT architecture and the bending-dominated cube architecture. Lastly, an ultralight HMM-integrated unmanned aerial vehicle (HMM-UAV) was successfully designed and printed. The HMM-UAV is ~85% lighter than its bulk counterpart, remarkably extending the flight duration time (~53%). This work not only provides an effective design strategy for HMMs but also further expands the application benchmark of HMMs.
The quality of the exposed avionics solder joints has a significant impact on the stable operation of the in-orbit spacecrafts. Nevertheless, the previously reported inspection methods for multi-scale solder joint defects generally suffer low accuracy and slow detection speed. Herein, a novel real-time detector VMMAO-YOLO is demonstrated based on variable multi-scale concurrency and multi-depth aggregation network (VMMANet) backbone and “one-stop” global information gather-distribute (OS-GD) module. Combined with infrared thermography technology, it can achieve fast and high-precision detection of both internal and external solder joint defects. Specifically, VMMANet is designed for efficient multi-scale feature extraction, which mainly comprises variable multi-scale feature concurrency (VMC) and multi-depth feature aggregation-alignment (MAA) modules. VMC can extract multi-scale features via multiple fix-sized and deformable convolutions, while MAA can aggregate and align multi-depth features on the same order for feature inference. This allows the low-level features with more spatial details to be transmitted in depth-wise, enabling the deeper network to selectively utilize the preceding inference information. The VMMANet replaces inefficient high-density deep convolution by increasing the width of intermediate feature levels, leading to a salient decline in parameters. The OS-GD is developed for efficacious feature extraction, aggregation and distribution, further enhancing the global information gather and deployment capability of the network. On a self-made solder joint image data set, the VMMAO-YOLO achieves a mean average precision mAP@0.5 of 91.6%, surpassing all the mainstream YOLO-series models. Moreover, the VMMAO-YOLO has a body size of merely 19.3 MB and a detection speed up to 119 frame per second, far superior to the prevalent YOLO-series detectors.