Mechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

The fault diagnosis of bearings is crucial in ensuring the reliability of rotating machinery. Deep neural networks have provided unprecedented opportunities to condition monitoring from a new perspective due to the powerful ability in learning fault-related knowledge. However, the inexplicability and low generalization ability of fault diagnosis models still bar them from the application. To address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings. The proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision tree methods by rebuilding the output decision layer of CNN according to the hierarchical structural characteristics of the decision tree, which is by no means a simple combination of the two models. The proposed DCTN model has unique advantages in 1) the hierarchical structure that can support more accuracy and comprehensive fault diagnosis, 2) the better interpretability of the model output with hierarchical decision making, and 3) more powerful generalization capabilities for the samples across fault severities. The multiclass fault diagnosis case and cross-severity fault diagnosis case are executed on a multicondition aeronautical bearing test rig. Experimental results can fully demonstrate the feasibility and superiority of the proposed method.

Legged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

Machine tools are one of the most representative machining systems in manufacturing. The energy consumption of machine tools has been a research hotspot and frontier for green low-carbon manufacturing. However, previous research merely regarded the material removal (MR) energy as useful energy consumption and ignored the useful energy consumed by thermal control (TC) for maintaining internal thermal stability and machining accuracy. In pursuit of energy-efficient, high-precision machining, more attention should be paid to the energy consumption of TC and the coupling relationship between MR and TC. Hence, the cutting energy efficiency model considering the coupling relationship is established based on the law of conservation of energy. An index of energy consumption ratio of TC is proposed to characterize its effect on total energy usage. Furthermore, the heat characteristics are analyzed, which can be adopted to represent machining accuracy. Experimental study indicates that TC is the main energy-consuming process of the precision milling machine tool, which overwhelms the energy consumption of MR. The forced cooling mode of TC results in a 7% reduction in cutting energy efficiency. Regression analysis shows that heat dissipation positively contributes 54.1% to machining accuracy, whereas heat generation negatively contributes 45.9%. This paper reveals the coupling effect of MR and TC on energy efficiency and machining accuracy. It can provide a foundation for energy-efficient, high-precision machining of machine tools.

When free-floating space robots perform space tasks, the satellite base attitude is disturbed by the dynamic coupling. The disturbance of the base orientation may affect the communication between the space robot and the control center on earth. In this paper, the enhanced bidirectional approach is proposed to plan the manipulator trajectory and eliminate the final base attitude variation. A novel acceleration level state equation for the nonholonomic problem is proposed, and a new intermediate variable-based Lyapunov function is derived and solved for smooth joint trajectory and restorable base trajectories. In the method, the state equation is first proposed for dual-arm robots with and without end constraints, and the system stability is analyzed to obtain the system input. The input modification further increases the system stability and simplifies the calculation complexity. Simulations are carried out in the end, and the proposed method is validated in minimizing final base attitude change and trajectory smoothness. Moreover, the minute internal force during the coordinated operation and the considerable computing efficiency increases the feasibility of the method during space tasks.

3D metal printing process has attracted increasing attention in recent years due to advantages, such as flexibility and rapid prototyping. This study aims to investigate the orientation effect of electropolishing characteristics on different surfaces of 316L stainless steel fabricated by laser powder bed fusion (L-PBF), considering that the rough surface of 3D printed parts is a key factor limiting its applications in the industry. The electropolishing characteristics on the different surfaces corresponding to the building orientation in selective laser melting are studied. Experimental results show that electrolyte temperature has critical importance on the electropolishing, especially for the vertical direction to the layering plane. The finish of electropolished surfaces is affected by the defects generated during L-PBF process. Thus, the electropolished vertical surface has higher surface roughness Sa than the horizontal surface. The X-ray photoelectron spectroscopy spectra show that the electropolished horizontal surface has higher Cr/Fe element ratio than the vertical surface. The electropolished horizontal surface presents higher corrosion resistance than the vertical surface by measuring the anodic polarization curves and fitting the equivalent circuit of experimental electrochemical impedance spectroscopy.

Product innovation is often a process for improving existing products. Low-end disruptive innovation (LDI) enables a product to meet the most price-sensitive customers in the low-end market. The existing LDI methods are mainly based on unnecessary characteristics of disruptive innovations. Thus, they cannot easily identify and respond to the LDI design needs. This study proposes a hybrid method for the product LDI in two levels of the product design based on the summarized definition and essential characteristics of LDI. Feasible areas of the product LDI are determined using a hybrid relational function model to identify the maturity of dominant technologies. The technologies are identified through the technical search and evaluation of the feasible area for innovation to form an initial LDI scheme. Then, the product function is optimized using the trimming concept of theory of inventive problem solving based on the characteristics of LDI. The final LDI scheme is formed and evaluated based on the essential characteristics of the product LDI. The feasibility of the proposed method is verified in the design of a new dropping pill machine.

Cutting fluid plays a cooling–lubrication role in the cutting of metal materials. However, the substantial usage of cutting fluid in traditional flood machining seriously pollutes the environment and threatens the health of workers. Environmental machining technologies, such as dry cutting, minimum quantity lubrication (MQL), and cryogenic cooling technology, have been used as substitute for flood machining. However, the insufficient cooling capacity of MQL with normal-temperature compressed gas and the lack of lubricating performance of cryogenic cooling technology limit their industrial application. The technical bottleneck of mechanical–thermal damage of difficult-to-cut materials in aerospace and other fields can be solved by combining cryogenic medium and MQL. The latest progress of cryogenic minimum quantity lubrication (CMQL) technology is reviewed in this paper, and the key scientific issues in the research achievements of CMQL are clarified. First, the application forms and process characteristics of CMQL devices in turning, milling, and grinding are systematically summarized from traditional settings to innovative design. Second, the cooling–lubrication mechanism of CMQL and its influence mechanism on material hardness, cutting force, tool wear, and workpiece surface quality in cutting are extensively revealed. The effects of CMQL are systematically analyzed based on its mechanism and application form. Results show that the application effect of CMQL is better than that of cryogenic technology or MQL alone. Finally, the prospect, which provides basis and support for engineering application and development of CMQL technology, is introduced considering the limitations of CMQL.

Energy field-assisted machining technology has the potential to overcome the limitations of machining difficult-to-machine metal materials, such as poor machinability, low cutting efficiency, and high energy consumption. High-speed dry milling has emerged as a typical green processing technology due to its high processing efficiency and avoidance of cutting fluids. However, the lack of necessary cooling and lubrication in high-speed dry milling makes it difficult to meet the continuous milling requirements for difficult-to-machine metal materials. The introduction of advanced energy-field-assisted green processing technology can improve the machinability of such metallic materials and achieve efficient precision manufacturing, making it a focus of academic and industrial research. In this review, the characteristics and limitations of high-speed dry milling of difficult-to-machine metal materials, including titanium alloys, nickel-based alloys, and high-strength steel, are systematically explored. The laser energy field, ultrasonic energy field, and cryogenic minimum quantity lubrication energy fields are introduced. By analyzing the effects of changing the energy field and cutting parameters on tool wear, chip morphology, cutting force, temperature, and surface quality of the workpiece during milling, the superiority of energy-field-assisted milling of difficult-to-machine metal materials is demonstrated. Finally, the shortcomings and technical challenges of energy-field-assisted milling are summarized in detail, providing feasible ideas for realizing multi-energy field collaborative green machining of difficult-to-machine metal materials in the future.

This study traces the development of dexterous hand research and proposes a novel antagonistic variable stiffness dexterous finger mechanism to improve the safety of dexterous hand in unpredictable environments, such as unstructured or man-made operational errors through comprehensive consideration of cost, accuracy, manufacturing, and application. Based on the concept of mechanical passive compliance, which is widely implemented in robots for interactions, a finger is dedicated to improving mechanical robustness. The finger mechanism not only achieves passive compliance against physical impacts, but also implements the variable stiffness actuator principle in a compact finger without adding supererogatory actuators. It achieves finger stiffness adjustability according to the biologically inspired stiffness variation principle of discarding some mobilities to adjust stiffness. The mechanical design of the finger and its stiffness adjusting methods are elaborated. The stiffness characteristics of the finger joint and the actuation unit are analyzed. Experimental results of the finger joint stiffness identification and finger impact tests under different finger stiffness presets are provided to verify the validity of the model. Fingers have been experimentally proven to be robust against physical impacts. Moreover, the experimental part verifies that fingers have good power, grasping, and manipulation performance.

Selective laser melting (SLM) is a unique additive manufacturing (AM) category that can be used to manufacture mechanical parts. It has been widely used in aerospace and automotive using metal or alloy powder. The build orientation is crucial in AM because it affects the as-built part, including its part accuracy, surface roughness, support structure, and build time and cost. A mechanical part is usually composed of multiple surface features. The surface features carry the production and design knowledge, which can be utilized in SLM fabrication. This study proposes a method to determine the build orientation of multi-feature mechanical parts (MFMPs) in SLM. First, the surface features of an MFMP are recognized and grouped for formulating the particular optimization objectives. Second, the estimation models of involved optimization objectives are established, and a set of alternative build orientations (ABOs) is further obtained by many-objective optimization. Lastly, a multi-objective decision making method integrated by the technique for order of preference by similarity to the ideal solution and cosine similarity measure is presented to select an optimal build orientation from those ABOs. The weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchy process. Two case studies are reported to validate the proposed method with numerical results, and the effectiveness comparison is presented. Physical manufacturing is conducted to prove the performance of the proposed method. The measured average sampling surface roughness of the most crucial feature of the bracket in the original orientation and the orientations obtained by the weighted sum model and the proposed method are 15.82, 10.84, and 10.62 μm, respectively. The numerical and physical validation results demonstrate that the proposed method is desirable to determine the build orientations of MFMPs with competitive results in SLM.

Earth rover is a class of emerging wheeled-leg robots for nature exploration. At present, few methods for these robots’ leg design utilize a side-mounted spatial parallel mechanism. Thus, this paper presents a complete design process of a novel 5-degree-of-freedom (5-DOF) hybrid leg mechanism for our quadruped earth rover BJTUBOT. First, a general approach is proposed for constructing the novel leg mechanism. Subsequently, by evaluating the basic locomotion task (LT) of the rover based on screw theory, we determine the desired motion characteristic of the side-mounted leg and carry out its two feasible configurations. With regard to the synthesis method of the parallel mechanism, a family of concise hybrid leg mechanisms using the 6-DOF limbs and an L_1F1C limb (which can provide a constraint force and a couple) is designed. In verifying the motion characteristics of this kind of leg, we select a typical (3-UPRU&RRRR)&R mechanism and then analyze its kinematic model, singularities, velocity mapping, workspace, dexterity, statics, and kinetostatic performance. Furthermore, the virtual quadruped rover equipped with this innovative leg mechanism is built. Various basic and specific LTs of the rover are demonstrated by simulation, which indicates that the flexibility of the legs can help the rover achieve multitasking.

With the proposal of intelligent mines, unmanned mining has become a research hotspot in recent years. In the field of autonomous excavation, environmental perception and excavation trajectory planning are two key issues because they have considerable influences on operation performance. In this study, an unmanned electric shovel (UES) is developed, and key robotization processes consisting of environment modeling and optimal excavation trajectory planning are presented. Initially, the point cloud of the material surface is collected and reconstructed by polynomial response surface (PRS) method. Then, by establishing the dynamical model of the UES, a point to point (PTP) excavation trajectory planning method is developed to improve both the mining efficiency and fill factor and to reduce the energy consumption. Based on optimal trajectory command, the UES performs autonomous excavation. The experimental results show that the proposed surface reconstruction method can accurately represent the material surface. On the basis of reconstructed surface, the PTP trajectory planning method rapidly obtains a reasonable mining trajectory with high fill factor and mining efficiency. Compared with the common excavation trajectory planning approaches, the proposed method tends to be more capable in terms of mining time and energy consumption, ensuring high-performance excavation of the UES in practical mining environment.

Transfemoral amputees (TAs) have difficulty in mobility during walking, such as restricted movement of lower extremity and body instability, yet few transfemoral prostheses have explored human-like multiple motion characteristics by simple structures to fit the kinesiology, biomechanics, and stability of human lower extremity. In this work, the configurations of transfemoral prosthetic mechanism are synthesized in terms of human lower-extremity kinesiology. A hybrid transfemoral prosthetic (HTP) mechanism with multigait functions is proposed to recover the gait functions of TAs. The kinematic and mechanical performances of the designed parallel mechanism are analyzed to verify their feasibility in transfemoral prosthetic mechanism. Inspired by motion–energy coupling relationship of the knee, a wearable energy-damper clutched device that can provide energy in knee stance flexion to facilitate the leg off from the ground and can impede the leg’s swing velocity for the next stance phase is proposed. Its co-operation with the springs in the prismatic pairs enables the prosthetic mechanism to have the energy recycling ability under the gait rhythm of the knee joint. Results demonstrate that the designed HTP mechanism can replace the motion functions of the knee and ankle to realize its multimode gait and effectively decrease the peak power of actuators from 94.74 to 137.05 W while maintaining a good mechanical adaptive stability.

Owing to their inherent great flexibility, good compliance, excellent adaptability, and safe interactivity, soft robots have shown great application potential. The advantages of light weight, high efficiency, non-polluting characteristic, and environmental adaptability provide pneumatic soft robots an important position in the field of soft robots. In this paper, a soft robot with 10 soft modules, comprising three uniformly distributed endoskeleton pneumatic artificial muscles, was developed. The robot can achieve flexible motion in 3D space. A novel kinematic modeling method for variable-curvature soft robots based on the minimum energy method was investigated, which can accurately and efficiently analyze forward and inverse kinematics. Experiments show that the robot can be controlled to move to the desired position based on the proposed model. The prototype and modeling method can provide a new perspective for soft robot design, modeling, and control.

This paper presents an extended model predictive control (MPC) scheme for implementing optimal path following of autonomous vehicles, which has multiple constraints and an integrated model of vehicle and road dynamics. Road curvature and inclination factors are used in the construction of the vehicle dynamic model to describe its lateral and roll dynamics accurately. Sideslip, rollover, and vehicle envelopes are used as multiple constraints in the MPC controller formulation. Then, an extended MPC method solved by differential evolution optimization algorithm is proposed to realize optimal smooth path following based on driving path features. Finally, simulation and real experiments are carried out to evaluate the feasibility and the effectiveness of the extended MPC scheme. Results indicate that the proposed method can obtain the smooth transition to follow the optimal drivable path and satisfy the lateral dynamic stability and environmental constraints, which can improve the path following quality for better ride comfort and road availability of autonomous vehicles.

This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains. The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles, and to improve its stability and safety when walking on complex terrain. By relying on the depth camera installed on the robot and obtaining the terrain heightmap, the algorithm converts the discrete grid heightmap into a continuous costmap. Then, it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion. Compared with most existing footholds selection algorithms that rely on discrete enumeration search, as far as we know, the proposed algorithm is the first to use a continuous optimization method. We successfully implemented the algorithm on a hexapod robot, and verified its feasibility in a walking experiment on a complex terrain.

The inverse kinematics problems of robots are usually decomposed into several Paden–Kahan subproblems based on the product of exponential model. However, the simple combination of subproblems cannot solve all the inverse kinematics problems, and there is no common approach to solve arbitrary three-joint subproblems in an arbitrary postural relationship. The novel algebraic geometric (NAG) methods that obtain the general closed-form inverse kinematics for all types of three-joint subproblems are presented in this paper. The geometric and algebraic constraints are used as the conditions precedent to solve the inverse kinematics of three-joint subproblems. The NAG methods can be applied in the inverse kinematics of three-joint subproblems in an arbitrary postural relationship. The inverse kinematics simulations of all three-joint subproblems are implemented, and simulation results indicating that the inverse solutions are consistent with the given joint angles validate the general closed-form inverse kinematics. Huaque III minimally invasive surgical robot is used as the experimental platform for the simulation, and a master–slave tracking experiment is conducted to verify the NAG methods. The simulation result shows the inverse solutions and six sets given joint angles are consistent. Additionally, the mean and maximum of the master–slave tracking experiment for the closed-form solution are 0.1486 and 0.4777 mm, respectively, while the mean and maximum of the master–slave tracking experiment for the compensation method are 0.3188 and 0.6394 mm, respectively. The experiments results demonstrate that the closed-form solution is superior to the compensation method. The results verify the proposed general closed-form inverse kinematics based on the NAG methods.

Aerospace aluminum alloy is the most used structural material for rockets, aircraft, spacecraft, and space stations. The deterioration of surface integrity of dry machining and the insufficient heat transfer capacity of minimal quantity lubrication have become the bottleneck of lubrication and heat dissipation of aerospace aluminum alloy. However, the excellent thermal conductivity and tribological properties of nanofluids are expected to fill this gap. The traditional milling force models are mainly based on empirical models and finite element simulations, which are insufficient to guide industrial manufacturing. In this study, the milling force of the integral end milling cutter is deduced by force analysis of the milling cutter element and numerical simulation. The instantaneous milling force model of the integral end milling cutter is established under the condition of dry and nanofluid minimal quantity lubrication (NMQL) based on the dual mechanism of the shear effect on the rake face of the milling cutter and the plow cutting effect on the flank surface. A single factor experiment is designed to introduce NMQL and the milling feed factor into the instantaneous milling force coefficient. The average absolute errors in the prediction of milling forces for the NMQL are 13.3%, 2.3%, and 7.6% in the x-, y-, and z-direction, respectively. Compared with the milling forces obtained by dry milling, those by NMQL decrease by 21.4%, 17.7%, and 18.5% in the x-, y-, and z-direction, respectively.

Aiming at the exploration and resource utilization activities on the Moon, in situ resource utilization and in situ manufacturing are proposed to minimize the dependence on the ground transportation supplies. In this paper, a laser-assisted additive manufacturing process is developed to fabricate lunar regolith composites with PA12/SiO₂ mixing powders. The process parameters and composite material compositions are optimized in an appropriate range through orthogonal experiments to establish the relationship of process–structure–property for lunar regolith composites. The optimal combination of composite material compositions and process parameters are mixing ratio of 50/50 in volume, laser power of 30 W, scanning speed of 3500 mm/s, and scanning hatch space of 0.2 mm. The maximum tensile strength of lunar regolith composites reaches 9.248 MPa, and the maximum depth of surface variation is 120.79 μm, which indicates poor powder fusion and sintering quality. Thereafter, the mechanical properties of laser-sintered lunar regolith composites are implemented to the topology optimization design of complex structures. The effectiveness and the feasibility of this laser-assisted process are potentially developed for future lightweight design and manufacturing of the solar panel installed on the lunar rover.

The flat clinching process is attracting a growing attention in the joining field of lightweight materials because it avoids the geometric protrusion that appears in the conventional clinching process. In this paper, the effects of sheet thickness and material on the mechanical properties of the clinched joint were studied. Al1060 and Al2024 sheets with 2 mm thickness were employed to develop the clinched joint by using different material configurations, and Al1060 sheets with 2.5- and 1.5-mm thicknesses were used to produce the clinched joint by using different thickness configurations. The clinched joints using various sheet configurations were sectioned, and dimensional analysis was conducted. Cross-tensile and shearing tests were carried out to analyze the mechanical properties of the clinched joint, including tensile strength, shearing strength, and absorbed energy. In addition, the failure modes of the clinched joints were discussed. Results indicated that the clinched joint with a stiff top sheet had increased static strength regardless of the test type. The clinched joint with a thick top sheet demonstrated lower static strength than the joint with a thick bottom sheet in the cross-tensile test. However, this result was reversed in the shearing tests. The flat clinching process has a great potential in joining dissimilar and various thickness materials.

Axial piston pumps have wide applications in hydraulic systems for power transmission. Their condition monitoring and fault diagnosis are essential in ensuring the safety and reliability of the entire hydraulic system. Vibration and discharge pressure signals are two common signals used for the fault diagnosis of axial piston pumps because of their sensitivity to pump health conditions. However, most of the previous fault diagnosis methods only used vibration or pressure signal, and literatures related to multi-sensor data fusion for the pump fault diagnosis are limited. This paper presents an end-to-end multi-sensor data fusion method for the fault diagnosis of axial piston pumps. The vibration and pressure signals under different pump health conditions are fused into RGB images and then recognized by a convolutional neural network. Experiments were performed on an axial piston pump to confirm the effectiveness of the proposed method. Results show that the proposed multi-sensor data fusion method greatly improves the fault diagnosis of axial piston pumps in terms of accuracy and robustness and has better diagnostic performance than other existing diagnosis methods.

Fiber-reinforced composites have become the preferred material in the fields of aviation and aerospace because of their high-strength performance in unit weight. The composite components are manufactured by near net-shape and only require finishing operations to achieve final dimensional and assembly tolerances. Milling and grinding arise as the preferred choices because of their precision processing. Nevertheless, given their laminated, anisotropic, and heterogeneous nature, these materials are considered difficult-to-machine. As undesirable results and challenging breakthroughs, the surface damage and integrity of these materials is a research hotspot with important engineering significance. This review summarizes an up-to-date progress of the damage formation mechanisms and suppression strategies in milling and grinding for the fiber-reinforced composites reported in the literature. First, the formation mechanisms of milling damage, including delamination, burr, and tear, are analyzed. Second, the grinding mechanisms, covering material removal mechanism, thermal mechanical behavior, surface integrity, and damage, are discussed. Third, suppression strategies are reviewed systematically from the aspects of advanced cutting tools and technologies, including ultrasonic vibration-assisted machining, cryogenic cooling, minimum quantity lubrication (MQL), and tool optimization design. Ultrasonic vibration shows the greatest advantage of restraining machining force, which can be reduced by approximately 60% compared with conventional machining. Cryogenic cooling is the most effective method to reduce temperature with a maximum reduction of approximately 60%. MQL shows its advantages in terms of reducing friction coefficient, force, temperature, and tool wear. Finally, research gaps and future exploration directions are prospected, giving researchers opportunity to deepen specific aspects and explore new area for achieving high precision surface machining of fiber-reinforced composites.

Servo-hydraulic actuators (SHAs) are widely used in mechanical equipment to drive heavy-duty mechanisms. However, their energy efficiency is low, and their motion characteristics are inevitably affected by uncertain nonlinearities. Electromechanical actuators (EMAs) possess superior energy efficiency and motion characteristics. However, they cannot easily drive heavy-duty mechanisms because of weak bearing capacity. This study proposes and designs a novel electromechanical-hydraulic hybrid actuator (EMHA) that integrates the advantages of EMA and SHA. EMHA mainly features two transmission mechanisms. The piston of the hydraulic transmission mechanism and the ball screw pair of the electromechanical transmission mechanism are mechanically fixed together through screw bolts, realizing the integration of two types of transmission mechanisms. The control scheme of the electromechanical transmission mechanism is used for motion control, and the hydraulic transmission mechanism is used for power assistance. Then, the mathematical model, structure, and parameter design of the new EMHA are studied. Finally, the EMHA prototype and test platform are manufactured. The test results prove that the EMHA has good working characteristics and high energy efficiency. Compared with the valve-controlled hydraulic cylinder system, EMHA exhibits a velocity tracking error and energy consumption reduced by 49.7% and 54%, respectively, under the same working conditions.

With the widespread application of legged robot in various fields, the demand for a robot with high locomotion and manipulation ability is increasing. Adding an extra arm is a useful but general method for a legged robot to obtain manipulation ability. Hence, this paper proposes a novel hexapod robot with two integrated leg–arm limbs that obtain dexterous manipulation functions besides locomotion ability without adding an extra arm. The manipulation modes can be divided into coordinated manipulation condition and single-limb manipulation condition. The former condition mainly includes fixed coordinated clamping case and fixed coordinated shearing case. For the fixed coordinated clamping case, the degrees of freedom (DOFs) analysis of equivalent parallel mechanism by using screw theory and the constraint equation of two integrated limbs are established. For the fixed coordinated shearing case, the coordinated working space is determined, and an ideal coordinated manipulation ball is presented to guide the coordinated shearing task. In addition, the constraint analysis of two adjacent integrated limbs is performed. Then, mobile manipulation with one integrated leg–arm limb while using pentapod gait is discussed as the single-limb manipulation condition, including gait switching analysis between hexapod gait and pentapod gait, different pentapod gaits analysis, and a complex six-DOF manipulation while walking. Corresponding experiments are implemented, including clamping tasks with two integrated limbs, coordinated shearing task by using two integrated limbs, and mobile manipulation with pentapod gait. This robot provides a new approach to building a multifunctional locomotion platform.

Bone grinding is an essential and vital procedure in most surgical operations. Currently, the insufficient cooling capacity of dry grinding, poor visibility of drip irrigation surgery area, and large grinding force leading to high grinding temperature are the technical bottlenecks of micro-grinding. A new micro-grinding process called ultrasonic vibration-assisted nanoparticle jet mist cooling (U-NJMC) is innovatively proposed to solve the technical problem. It combines the advantages of ultrasonic vibration (UV) and nanoparticle jet mist cooling (NJMC). Notwithstanding, the combined effect of multi parameter collaborative of U-NJMC on cooling has not been investigated. The grinding force, friction coefficient, specific grinding energy, and grinding temperature under dry, drip irrigation, UV, minimum quantity lubrication (MQL), NJMC, and U-NJMC micro-grinding were compared and analyzed. Results showed that the minimum normal grinding force and tangential grinding force of U-NJMC micro-grinding were 1.39 and 0.32 N, which were 75.1% and 82.9% less than those in dry grinding, respectively. The minimum friction coefficient and specific grinding energy were achieved using U-NJMC. Compared with dry, drip, UV, MQL, and NJMC grinding, the friction coefficient of U-NJMC was decreased by 31.3%, 17.0%, 19.0%, 9.8%, and 12.5%, respectively, and the specific grinding energy was decreased by 83.0%, 72.7%, 77.8%, 52.3%, and 64.7%, respectively. Compared with UV or NJMC alone, the grinding temperature of U-NJMC was decreased by 33.5% and 10.0%, respectively. These results showed that U-NJMC provides a novel approach for clinical surgical micro-grinding of biological bone.

In fiber laser beam welding (LBW), the selection of optimal processing parameters is challenging and plays a key role in improving the bead geometry and welding quality. This study proposes a multi-objective optimization framework by combining an ensemble of metamodels (EMs) with the multi-objective artificial bee colony algorithm (MOABC) to identify the optimal welding parameters. An inverse proportional weighting method that considers the leave-one-out prediction error is presented to construct EM, which incorporates the competitive strengths of three metamodels. EM constructs the correlation between processing parameters (laser power, welding speed, and distance defocus) and bead geometries (bead width, depth of penetration, neck width, and neck depth) with average errors of 10.95%, 7.04%, 7.63%, and 8.62%, respectively. On the basis of EM, MOABC is employed to approximate the Pareto front, and verification experiments show that the relative errors are less than 14.67%. Furthermore, the main effect and the interaction effect of processing parameters on bead geometries are studied. Results demonstrate that the proposed EM-MOABC is effective in guiding actual fiber LBW applications.

Ceramic structural parts are one of the most widely utilized structural parts in the industry. However, they usually contain defects following the pressing process, such as burrs. Therefore, additional trimming is usually required, despite the deformation challenges and difficulty in positioning. This paper proposes an ultrafast laser processing system for trimming complex ceramic structural parts. Opto-electromechanical cooperative control software is developed to control the laser processing system. The trimming problem of the ceramic cores used in aero engines is studied. The regional registration method is introduced based on the iterative closest point algorithm to register the path extracted from the computer-aided design model with the deformed ceramic core. A zonal and layering processing method for three-dimensional contours on complex surfaces is proposed to generate the working data of high-speed scanning galvanometer and the computer numerical control machine tool, respectively. The results show that the laser system and the method proposed in this paper are suitable for trimming complex non-datum parts such as ceramic cores. Compared with the results of manual trimming, the method proposed in this paper has higher accuracy, efficiency, and yield. The method mentioned above has been used in practical application with satisfactory results.

Capacitive sensors are efficient tools for biophysical force measurement, which is essential for the exploration of cellular behavior. However, attention has been rarely given on the influences of external mechanical and internal electrical interferences on capacitive sensors. In this work, a bionic swallow structure design norm was developed for mechanical decoupling, and the influences of structural parameters on mechanical behavior were fully analyzed and optimized. A bionic feather comb distribution strategy and a portable readout circuit were proposed for eliminating electrostatic interferences. Electrostatic instability was evaluated, and electrostatic decoupling performance was verified on the basis of a novel measurement method utilizing four complementary comb arrays and application-specific integrated circuit readouts. An electrostatic pulling experiment showed that the bionic swallow structure hardly moved by 0.770 nm, and the measurement error was less than 0.009% for the area-variant sensor and 1.118% for the gap-variant sensor, which can be easily compensated in readouts. The proposed sensor also exhibited high resistance against electrostatic rotation, and the resulting measurement error dropped below 0.751%. The rotation interferences were less than 0.330 nm and (1.829 × 10⁻⁷)°, which were 35 times smaller than those of the traditional differential one. Based on the proposed bionic decoupling method, the fabricated sensor exhibited overwhelming capacitive sensitivity values of 7.078 and 1.473 pF/µm for gap-variant and area-variant devices, respectively, which were the highest among the current devices. High immunity to mechanical disturbances was maintained simultaneously, i.e., less than 0.369% and 0.058% of the sensor outputs for the gap-variant and area-variant devices, respectively, indicating its great performance improvements over existing devices and feasibility in ultralow biomedical force measurement.

Seven-degree-of-freedom redundant manipulators with link offset have many advantages, including obvious geometric significance and suitability for configu-ration control. Their configuration is similar to that of the experimental module manipulator (EMM) in the Chinese Space Station Remote Manipulator System. However, finding the analytical solution of an EMM on the basis of arm angle parameterization is difficult. This study proposes a high-precision, semi-analytical inverse method for EMMs. Firstly, the analytical inverse kinematic solution is established based on joint angle parameterization. Secondly, the analytical inverse kinematic solution for a non-offset spherical–roll–spherical (SRS) redundant manipulator is derived based on arm angle parameterization. The approximate solution of the EMM is calculated in accordance with the relationship between the joint angles of the EMM and the SRS manipulator. Thirdly, the error is corrected using a numerical method through the analytical inverse solution based on joint angle parameterization. After selecting the stride and termination condition, the precise inverse solution is computed for the EMM based on arm angle parameterization. Lastly, case solutions confirm that this method has high precision, and the arm angle parameterization method is superior to the joint angle parameterization method in terms of parameter selection.