Robot-assisted surgery aims to assist surgeons in performing surgical procedures through robotic systems, and it has attracted increasing attention in recent years. The rapid development of artificial intelligence (AI) has accelerated the progress of robot-assisted surgery towards minimally invasive, intelligent, and autonomous capabilities. This research provides a comprehensive review of the application of AI in robot-assisted surgery, summarizing three main aspects: medical image processing, surgical planning and navigation, and motion control and decision-making. Leveraging AI technology, the application of medical image processing enables physicians to obtain more precise, higher-definition, and visually intuitive imaging data. It allows for accurate segmentation and alignment of lesions and tissues, as well as automated recognition and analysis of pathological or abnormal areas within medical images. The application of AI in surgical planning and navigation allows surgeons to precisely plan surgical procedures and provide accurate navigation guidance. By integrating personalized patient data and the extensive experience of surgeons, AI assists in predicting surgical risks and provides real-time guidance for precise localization and skillful manipulation during the surgery. Moreover, the application of AI in surgical robot motion control and decision-making enables robots to execute tasks more efficiently and make intelligent decisions. AI algorithms can analyze complex information in the surgical environment in real-time, facilitating precise motion control for the robot. Finally, this research also analyzes the development opportunities and challenges of AI in robot-assisted surgery, offering guidance and insights for future research in the field.

Considering the residual stress of tooth surface produced by carburizing, tooth grinding and shot peening, the complex stress field of tooth surface contact stress and residual stress is established, and a method for calculating contact fatigue crack initiation and propagation life of spiral bevel gears is proposed. A gear finite element contact analysis model is established to calculate the multi-axis alternating contact stress field. Considering the complexity of residual stress distribution of space spiral surface, the tooth surface with variable curvature is discretized into network nodes. The residual stress field of tooth surface is established by measuring the surface and sub-surface residual stress. Based on Dang Van criterion, a tooth surface crack initiation model is established. Considering the residual stress and crack closure effect, a model of tooth surface crack propagation is established, and the gear contact fatigue life under compound stress field is calculated. The results show that the spatial curvature of tooth surface affects the distribution of residual stress caused by shot peening, and the residual compressive stress in the central region is about 20% higher than that in the edge region. The crack initiation location and the fatigue life of the tooth surface are mainly determined by the contact stress, and the residual stress will affect the average stress. The crack propagation life accounts for about 10% of the whole life, which indicates the failure to rapid fracture of gear contact fatigue. The research can be an important reference in the design of long life and high reliability gear transmission.

Introducing actuation redundancy in parallel kinematic machines can avoid singularities, improve stiffness and load. Redundant actuation, however, poses challenges to dynamics modeling and controller designing regarding internal force distribution and optimization. In order to solve the above problems, taking a Vex4 3-DOF parallel robot as an example, dynamics model is established based on the natural orthogonal complement method. Then, by resorting to the right Moore-Penrose generalized inverse, the solution of the minimum-actuating-force is obtained based on QR decomposition of coefficient matrix. To balance actuator-force and track trajectory, a synchronous optimization method is first proposed and then integrated into a force-position hybrid controller with non-redundant branch controlled by position law and redundant branch by force law. Finally, a prototype of Vex4 is built to test and verify the proposed modeling and controller designing approach.

Driven by the Carbon-peaking and Carbon-neutrality strategic goals, lithium-ion batteries usher in significant development opportunities. Meanwhile, it has become a research hotspot for tracking the life cycle carbon footprint and environmental indicators assessment and faced severe challenges in carbon emission calculation and reduction measures. First, the basic framework, methods,evaluation indicators, and other common problems of the life cycle assessment are briefly summarized. Then, a whole life cycle closed-loop assessment route from "cradle" to "cradle" is proposed for the sustainable development of lithium-ion batteries. The research progress of carbon emission calculation at all stages of the battery life cycle(including battery production, battery use,echelon utilization, battery recycling, and remanufacture) is summarized in detail, the potential research hotspots and difficulties are generalized, and a comprehensive evaluation framework of "Technology-Ecology-Value" is proposed. The opportunities and challenges in lithium-ion batteries' life cycle value assessment are discussed, and the resource and supply chain risks are analyzed.Finally, six potential carbon reduction measures for the whole life cycle of lithium-ion batteries are summarized and prospected, such as energy decarbonization, system innovation, intelligent manufacturing, optimization management, material recovery, and carbon capture.

The research content is the motion planning of autonomous vehicles in extreme conditions, and a motion planning strategy for autonomous vehicles adapting to extreme conditions is proposed. Firstly, a dynamic model which can accurately describe the motion of vehicle is established, and a modified nonlinear tire model is used to reflect the mechanical properties between the tire and road surfaces. Secondly, an adaptive potential field model based on safe braking distance is proposed to adapt the change of external conditions and vehicle parameters in extreme conditions. Furthermore, considering the vehicle prone to lateral instability under extreme conditions, the lateral stability index(LSI) is designed as the key optimization parameter, and the lateral stability of vehicle is analyzed. Then, based on model predictive control(MPC) method, the motion planning problem in the extreme conditions is transformed into a multi-objective optimization problem. Finally, the PreScan-Simulink-CarSim co-simulation platform is built, and the proposed motion planning strategy is verified in various extreme conditions, such as snow and ice covered road. The simulation results show that the strategy effectively improves the safety and stability of the autonomous vehicle in the extreme conditions.

Path Tracking plays important role in the lateral control of autonomous vehicles. The stability and tracking accuracy are usually related to vehicle speed, road curvature, etc., which directly affect the safety in complex driving conditions. To improve the stability and tracking accuracy under complex conditions, path planning, tracking control and stability control are combined together to design a tracking control method based on adaptive preview paths. First, based on the vehicle's two-degree-of-freedom model, a preview distance adaptive algorithm is designed, which adjusts the preview distance according to the vehicle dynamics state and road adhesion. Secondly, the preview path at the desired preview distance is given by a cubic polynomial fitting method. Finally, based on performance of obstacle avoidance, tracking accuracy, and vehicle stability, a particle swarm optimization algorithm(PSO) is designed to optimize the algorithm parameters. The performances in path tracking, lane changing and obstacle avoidance conditions are verified in the hardware-in-the-loop tests and vehicle tests. The results show that the algorithm can adaptively adjust the preview path during tracking with low computation burden, and achieve the balance of tracking accuracy and vehicle stability.

Solar vapor generation is a reliable, environmentally friendly, inexpensive technology making use of solar energy by photothermal conversion progress. Photothermal conversion, heat management, water transport and vapor escape are integrated and finely designed for interfacial solar vapor generation (ISVG). With the aid of microstructural photonics, material modification, thermal structure design, mechanical design, ISVG system can absorb salty, polluted bulk water or even vapor from atmosphere and evaporate it to produce fresh water, mineral salt, energy efficiently and fast. ISVG technology has aroused great interest among researchers and made substantial progress. The working mechanism and component materials of ISVG system are briefly introduced. Macro/microstructure design and optimization strategies of photothermal conversion, heat management, water transport, and vapor escape are summarized. The peripherals of ISVG are shown by introducing detailed applications. Finally, the conclusions and outlook of ISVG are summarized.

The impact features in the vibration signal of rotating machinery usually represent the occurrence of common faults such as bearing damage and gear damage. In order to accurately extract the impact component in the signal, a time-frequency analysis method based on improved time-reassignment synchrosqueezing transform(TSST) is proposed. Firstly, the characteristics of TSST prototype algorithm in dealing with actual strongly frequency varying signals are analysed, and it is found that it is easy to cause evident time-frequency ambiguity. Then, an improved group delay estimation method based on local maximum search algorithm is constructed to overcome the time-frequency ambiguity problem caused by TSST. On this basis, an adaptive group delay estimation strategy is proposed. Finally, an adaptive synchrosqueezing transform method based on improved group delay estimation is formed, and a pulse feature extraction method in vibration signal is developed. The results of simulation and experimental data show that the proposed method can extract impulse features of vibration signals more accurately, and generate a more concentrated time-frequency representation than other time-frequency analysis methods.

As the key structure of the running gear of rail vehicles, the service safety of bogie frame has received great attention. Therefore, the newly designed bogie frame sample of metro vehicle is taken as the research object, and the fatigue damage and fatigue life are studied based on its dynamic stress in service. Combined with the vehicle running state data, the damage distribution characteristics of the bogie’s key parts are studied, the reasons for the rapid accumulation of fatigue damage are also analyzed. For the key parts of the bogie frame sample: the crack initiation life is calculated; the kernel density of stress amplitude distribution is estimated, which is based on the stress amplitude samples after rain flow counting; the crack propagation model is established; and by the use of Monte Carlo method and inverse function method, the cumulative failure probability under different operating mileage is calculated. The results show that the cumulative failure probability of the bogie frame increases rapidly with the increase of operating mileage, and the operating mileage corresponding to 97.5% reliability is 30,000 km after crack initiation; the fatigue life of the frame is the sum of crack initiation life and propagation life, and it is 483 900 km under 97.5% reliability. The research results provide a research basis for further improving the anti fatigue performance of the frame and optimizing the maintenance cycle of the bogie.

Aiming at the problem of large attitude estimation error of wall climbing robot due to the limited application of sensors in the relatively closed and magnetic interference environment, a new attitude estimation method based on inertial measurement unit(IMU) and cylindrical shape constraint is proposed and implemented. Taking advantage of the frequent switching between the moving and stationary states of the wall climbing robot, the angular velocity drift of IMU in the moving state is estimated using the angular velocity output of IMU in the stationary state. With the constant roll angle constrained by the cylinder surface, an extended Kalman filter(EKF) is designed to estimate the attitude of robot and the angular velocity drift of IMU in real time. The experimental results show that this method can reduce the heading angle error in attitude estimation from over 20°to 3.5°, and the pitch angle error is remained within 2ånd the roll angle error is less than 0.5°, which effectively improves the accuracy of the attitude estimation.

Based on the needs of item identification and operation in current smart home, and in view of the poor dexterity and accuracy of different poses of objects in existing household service robot, the research on robot hand-eye coordination recognition technology and item dexterous operation planning method are studied. In this paper, a recognition and multi-pose grasping method based on visual feedforward to locate three-dimensional position of target and visual feedback to match target pose is proposed.Firstly, SSD depth neural network model is used to identified items, and the three-dimensional position is carried out as the rough coordinate of the target. Then, the relative coordinate of the depth camera and the object is preset according to the obtained three-dimensional coordinates, and the depth information of the object and the obstacle is collected. At the same time, the pose matching is executed by comparing the built-in three-dimensional model with the accurate object by means of Linemod algorithm.Finally, according to the position and posture of the obtained objects and obstacles, the grasping posture of the arm control system is standardized to achieve the dexterous grasping of objects. From the above principles, Design hand-eye control experiments of tables at different heights to test success rate and grasping error by standardizing the position and process of item grabbing. As a result, there is a high successful rate, and the root mean square errors of grasping in three orientations are less than 0.006m. Therefore, it is applicable to the grasping and other operations of cube, column, sphere and other items; It is of great significance to the development of home service robot industry.

As an important research direction of the new robot, micro/nano robots have made a lot of achievements in the field of biomedicine. Especially micro/nano robots driven by the magnetic field are widely used in drug delivery because of its precise motion control and no direct contact with the controlled object. In recent years, due to the lack of in-situ culture system which can control the motion of magnetically driven micro-nano robots and provide suitable temperature environment for cell tissue at the same time, the application and research of micro/nano robots in promoting cell tissue regeneration are seriously restricted. A set of cells in situ culture system for magnetically driven micro-nano robots is designed to realize the in-situ culture and monitoring of cell tissue in the experiment of magnetically driven micro/nano robots. The temperature output of the system is realized by using the principle of air-cooled radiator in reverse. The non-isothermal flow simulation is carried out by COMSOL software. These simulation results show that the heating effect of the heating module and the heating capacity of the heating actuator could meet the demand. At the same time, the position of the inlet and outlet of the incubator was defined by these. Then the temperature control experiment verified that the system could achieve stable temperature control. The design of the system has strong practicability, wide applicability and guiding significance for the research of micro/nano robots in situ culture system.

Aiming at the problem that multi-UAV system is prone to collision when using finite-time ring formation algorithm to perform ring formation tasks, this paper proposes a multi-UAV finite-time ring formation control algorithm based on improved artificial potential field method. A set of auxiliary potential fields perpendicular to the direction of obstacle movement are introduced, which avoids the internal collision of multi-UAV in the process of rapid formation, and solves the problem that traditional artificial potential field method is easy to fall into local optimal solution. In order to verify the effectiveness of the proposed algorithm, computer simulation experiments are carried out under the same parameters such as the initial position of the UAV, the influence range of the potential field and the surrounding radius. The results show that the proposed algorithm can effectively avoid the collision of multiple UAVs in the ring formation process. In order to further verify the practicability of the algorithm, this paper uses three"X"rotor UAVs with axial distance of 450 mm to carry out physical experiments. The experimental results show that the proposed algorithm has good collision avoidance effect when completing the ring formation of multiple UAVs in limited time.

With the development of third-generation power semiconductor devices, the wide bandgap semiconductor chips represented by SiC are playing an increasingly important role in high-power power electronic devices. However, the packaging materials matched with traditional Si chips cannot meet their high-temperature service requirements and become a shortcoming in the application of power electronic devices. Nanoparticle materials used as an interlayer for electronic packaging can achieve low-temperature bonding and high-temperature service, which is a current research hotspot of packaging materials. This paper reviews the types of nanoparticle materials as the interlayer, focusing on the analysis of the advantages, influencing factors and limitations of nanoparticle of elementary substance for sintering-bonding, and systematically expounds the latest progress and development trend of composite nanoparticle for sintering-bonding, aiming to promote the application of nanoparticle material as an interlayer for electronic packaging.

Chemical mechanical planarization, known as CMP, is one of the key technologies in chip manufacturing and is widely used to achieve the ultrafine planarization of a variety of structures on the nanometer scale. The metals in interconnection layer exhibits quite different properties from the materials in other structures in chips, whose planarization relies more on the chemical components in the polishing slurry. The synergistic mechanism depicts the process of material removal in metal CMP:the surface of the interconnection layer is first chemically modified by the chemical components in the slurry, followed by the subsequent mechanical abrasion and then removed away. Based on the mechanism, the review highlights the contact mechanics which studies the microscopic states and functions of the abrasive particles and the developments of related models; elaborates the roles of the chemical components including oxidizers, complexing agents and inhibitors, and the process and principle of their reactions with metals; summarizes the latest progress and tendency of slurry development. It is expected that it could provide insight on the future slurry developed for new process and materials, so as to achieve the desired material removal rate, superfine planarization and ultra-low defects requirements under different situations during the rapid advancement of the semiconductor manufacturing.

In recent years, robot-based intelligent garage (RIG) has shown its effectiveness in alleviating the problem of "difficult parking" in cities with its high capacity, high efficiency, and high safety. The core component of a RIG is an automated guided vehicle (AGV), and the control of AGV operation relies on critical RIG technologies. Based on the analysis of RIG-related literature, the existing RIG technologies are firstly reviewed in terms of "layout scheme", "scheduling strategy" and "path planning", based on the operational characteristics of RIGs. The critical component technologies are reviewed. Then, the theoretical basis, research methods, application status, advantages and disadvantages of RIG critical technologies are systematically reviewed, and the important role played by RIG critical technologies in the operation process is thoroughly discussed. Finally, in view of the problems existing in the operation of RIG, the development trend of RIG critical technologies is still foreseen from the above three aspects. It is important to emphasize that ① Big data processing technology is used to tap into the parking demand at different time periods and guide the automatic optimization of RIG layout to balance the parking capacity and access efficiency demands; ② Cloud robotics is gradually being widely applied in RIG scheduling strategies, which are combined with the mobility-as-a-service technology RIG to develop RIG scheduling strategies that meet user satisfaction; ③ As RIG layout schemes, scheduling strategies and the complexity of the actual environmental obstacles, the use of deep reinforcement learning framework to solve the path planning problem of AGVs has become the current development trend. The systematization of the research results of critical RIG technologies is an important guide for future RIG technology development and engineering applications.

The SSRMS-type manipulators are widely used in space on-orbit services, but the inverse kinematics is difficult to solve due to redundancy and the existence of shoulder, axis, and wrist offsets. Although the joint angle parameterization method can obtain the analytical solution of inverse kinematics, the success rate is highly dependent on the given value of the parameter. The method based on the Jacobian matrix will reduce the kinematics performance of the manipulator when considering singularity avoidance. To solve these issues, an inverse kinematics solution method (CCDJAP-IK) based on the combination of the cyclic coordinate descent method and the joint angle parameterization method is proposed. This method has the advantages of being insensitive to Jacobian matrix singularities, avoiding joint limits, and finding multiple exact solutions. The approximate solution obtained based on the cyclic coordinate descent method is used as the given value of the parameter in the joint angle parameterization method, which reduces the blindness in determining parameter value and increases the success rate of the solution. The movement of the end effector is converted into the movement of the endpoint of the sixth joint restricted only in the y-axis direction, which simplifies the objective function and the iterative steps of the algorithm, and improves the calculation efficiency. Taking the HIT-SSRMS manipulator as an example, simulation experiments are carried out. The results show that:under the condition that the current configuration and the desired pose are randomly selected in the workspace, the average calculation time and the success rate of the CCDJAP-IK method are 4.86 ms and 99.32%, respectively, which is an effective and reliable method for solving the inverse kinematics of SSRMS-type manipulator. When tracking the Cartesian path, the tracking accuracy, joint space continuity, and real-time performance of the CCDJAP-IK method meet the task requirements, so it can be applied to the real-time path tracking task of the manipulators.

The high-end equipment in major engineering project usually served in harsh environment and complicated load conditions. To guarantee the structural integrity and service safety of the equipment, the influencing factors such as material properties, multi physical field loads, environment and complex geometric characteristics and mechanical structure strength design should be comprehensively evaluated. To acquire the significant parameters of material and mechanical structure in service environment, research on high-temperature mechanical test technology in harsh environment is carried out, so as to serve the independent design and manufacturing of key high-temperature components in the fields of nuclear power, aerospace, chemical energy and so on. High temperature mechanical test technology of domestic test equipment depends on high temperature mechanical test equipment. China began to develop domestic high-temperature mechanical test equipment in harsh environment in the 1980s. It focuses on the development process of domestic high-temperature mechanical test equipment in severe environment, summarizes and discusses the overall technical framework of high-temperature mechanical test equipment in severe environment, analyses in detail four types of key technologies involved in high-temperature mechanical test equipment in severe environment, and introduces the domestic high-temperature mechanical test equipment and characteristics of four types of typical severe environment. Finally, the future breakthrough of high temperature mechanical test technology under more severe conditions is prospected.

Multi-dimensional and multi-scale high-throughput characterization can effectively improve the development efficiency and significantly accelerate the industrialization process of advanced materials, which also serves as a scientific evidence for the reliable in-service assessment and entire lifetime management of engineering materials and structures. Firstly introduces the research background and fundamental concept of the multi-dimensional and multi-scale high-throughput characterization technology. The high-throughput sample preparation, multi-dimensional and multi-scale correlation tomography, in-situ high-throughput characterization technology are then summarized systematically. In addition, both current technological applications and limitations of the multi-dimensional and multi-scale high-throughput characterization technology are discussed in details. Finally, the technological challenges and future developing directions to the multi-dimensional and multi-scale high-throughput characterization technology are given to pursue the correlation between these problems and service performance of advanced materials and structures particularly subjected to extremely complex loading and environment conditions. This paper attempts to provide a basic reference to establish the quantitative relationship between the microstructural features and macro in-service performance, revealing the damage mechanism and failure mode of engineering components and promoting the development and application of advanced materials.

With the flourishing development of mechanical equipment, such as aerospace vehicle, high-speed train, nuclear power plant and wind turbine, the mechanical Structural Health Monitoring (SHM) which could ensure the high performance and reliability of mechanical structures has been universally emphasized. By SHM, the mechanical structure can be monitored online during the service process of structure. In addition, the scheduled maintenance can be replaced by the as-needed maintenance. As a result, the structural maintenance cost can be reduced while the safety and reliability of the mechanical structure can be ensured. A review of the critical aspects of the mechanical SHM is presented. First, the development status of mechanical SHM in aerospace, energy and chemical industry, wind turbine and high-speed railway is illustrated. Then, concerns regarding of the advanced sensing technology, SHM systems and SHM methods commonly used in mechanical SHM are presented and reviewed. Finally, the crucial points for further exploring methods and technologies of the mechanical SHM are summarized.

The research course and main contents of vehicle-pavement interactions are reviewed,and the relationship between three research fields of vehicle system dynamics,tire dynamics and pavement structure dynamics is analyzed. The research progress was reviewed from three levels,including random vibrations of vehicle and pavement-friendly suspensions,tire-pavement contact dynamics,pavement structure dynamics under dynamic load,thus proposing the problems existing in the research on vehicle-pavement interactions as well as the future development direction. Currently,research on vehicle-pavement interactions mostly focuses on a single field or the simple superposition of three fields,but ignoring or simplifying the complex dynamic coupling relationship between vehicle-pavement interactions and mutual restraints. However,to meet the higher control accuracy and dynamic performance optimization of vehicles,the interactions between vehicles and pavements need to be considered. As for the tire-pavement contact relationship,most of the existing researches are based on the specific parameters of the pavement to describe the hysteresis characteristics of the tire itself. The dynamic coupling characteristics between the tire and the pavement needs to be further studied. The simple pavement roughness model is insufficient to describe the topography of the pavement,which restricts the study of vehicle-pavement interactions. It is still significant to conduct the extraction,description and reconstruction of the pavement topography. The realization of vehicle motion control and the design of the controller mostly depend on the dynamic response of the mass center and the pavement adhesion. The vehicle-tire-pavement transient coupling mechanism as well as the high-precision and rapid identification of pavement parameters will be very theoretically difficult with huge engineering application prospects. In addition,the application of in-wheel motors in the new generation of intelligent electric vehicles has changed the chassis configuration and load distribution of vehicles. Considering the comprehensive effects of pavement random excitation,motor excitation and vehicle-pavement coupling excitation,research on vehicle-pavement interactions and intelligent control is also a challenging scientific issue.

The increase in the unsprung mass of the electric vehicle driven by the in-wheel motor enlarges the tire dynamic loads, and the electromagnetic force of the motor will aggravate the vehicle vibration too. In the meanwhile, the vehicle and the road are interacted with each other through dynamic tire forces. In order to explore the vibration mechanism of electric vehicles, a non-linear dynamic model of the mechanic-electro-road coupling system for the electric vehicle is established, which takes into account the non-linearity of suspension stiffness, damping and tire stiffness. Based on the traditional road surface irregularity excitation, the electromagnetic excitation of the in-wheel motor and the road secondary excitation caused by the vehicle-road coupling are also considered. The expression of the electromagnetic excitation of the motor is analytically deduced, the three-dimensional solid finite element model of the in-wheel motor is established, the magnetic flux distribution and electromagnetic torque are calculated, and the validity of the theoretical results is verified. The modal superposition method is used to derive the vertical displacement response of the viscoelastic beam on the foundation simply supported at both ends, which is the secondary excitation of the road considered in the coupled system model. Taking vehicle body acceleration, suspension dynamic deflection, tire force and tire quartic force as evaluation indicators, the effects of electromagnetic excitation, road secondary excitation, vehicle driving speed and vehicle nonlinearity on vehicle vibration and road friendliness are analyzed. It is shown that vehicle nonlinearity has the greatest impact on vehicle vibration and road friendliness, followed by electromagnetic excitation, and road surface secondary excitation; When the vehicle is running at higher speed, the vehicle body vibration intensifies and the impact of vehicle load on road damage is more significant; On the flatter road, the influences of the above three factors are more obvious. The proposed vehicle and motor, road and integrated modeling ideas can provide reference for the dynamic design of electric vehicles and road-friendliness research.

Due to gear clearances of automotive driveline, transient vibro-impacts between gear teeth easily cause serious noise and vibration problem during fast engagement clutch, which decrease the vehicle sound quality. To analyze the transient vibro-impacts of driveline system excited by fast engagement of the clutch, a 9 degree-of-freedom lumped parameter dynamical model with piecewise linear clearance elements and nonlinear friction element for a rear-wheel-drive vehicle driveline system is established based on nonlinear theory of clearance and friction. The transient vibro-impact phenomena of the vehicle driveline excited by fast engagement of the clutch are numerically simulated. The plane phase reveals the phenomenon of multiple impacts and rebounds of the gear teeth in each transient impact, and shows the relationship between the relative contact deformation of the gear teeth and the relative angular velocity. Compared to axle clearance element, the transmission clearance element produces the largest transient impact force and elastic potential energy. During speed synchronization of the flywheel and clutch, the friction torque and Stick-Slip phenomenon between flywheel and clutch plate with different normal force are analyzed. Compared to the widely used friction model based on Karnoop friction theory, the numerical friction model established in this paper can better simulate the driveline vibro-impact caused by speed synchronization and the friction torque between flywheel and clutch plate during clutch engagement. The numerical results are verified by the vehicle tests.

Intelligent manufacturing is the main direction of the future manufacturing industry, the high-end manufacturing equipments represented by aerospace and automobile fields are related to national defense security and national economic lifeline. The higher requirements for the management and control of cutting tools are put forward by complex and diversified machining of parts. As the most active and state-changing element in the cutting process, the performance of the tool directly affects the machining accuracy and productivity. The advent of the big data era has led to a change in the tool management paradigm, with manufacturers, suppliers and application companies demanding life-cycle data on tools. By analyzing the current situation of tool management and control, the design and manufacturing precision, the accuracy of life prediction and scientific tool management and control are issues that need to be addressed. The connotation and key technologies of the whole life-cycle intelligent management and control of tools are proposed, the research results of domestic and foreign scholars in tool design and manufacturing intelligent optimisation, tool cutting process condition monitoring and tool multi-source data management sharing are reviewed, and finally the future research directions are prospected in the light of the application of tool control technology. With the continuous deepening of intelligent manufacturing, the intelligent management and control of cutting tool life-cycle based on artificial intelligence, big data, digital twin, cloud computing and other modern information technology will certainly promote the transformation and upgrading of tool industry chain.

Bone is an anisotropic material with complex structure. Also, its processing is a basic technology in surgery. The quality of bone processing is the critical factor in surgical treatment effect, implant stability and postoperative recovery time. The mechanical properties of bone are varied from different parts of huma body. Moreover, there are many kinds of surgical instruments, which make the processing methods of bone materials diversified. And those surgical instruments need to process bone material with high precision, high efficiency and low damage. The research of bone cutting mechanism is of great significance to improve the performance of surgical instruments, surgical treatment and rehabilitation effect. Base on the basic characteristics of bone material, this review introduces the cutting mechanism of conventional (i.e. drilling, milling, grinding, sawing) and non-conventional (i.e. ultrasonic, laser, water/abrasive jet) bone processing, clarifying the development status of cutting force and cutting temperature models. Moreover, some existing problems are pointed out and the research thoughts on cutting mechanism of bone material are put forward in this review.

The demand for medical and health care gradually increases with the development of society, and precision medicine with its advantages of low risk and precise customized treatment has attracted attention from global researchers. The precision medicine instruments come in various types, e.g. microscopic surgical tools and wearable sensors, which contact human tissues, cells and biological mucus during operation, and form bio-instrument contact interfaces with complicated physical/chemical properties. Due to the change of instrument types, operating environments and contact states, the bio-instrument contact interfaces have growing requirements in diverse functions, such as the securing fixation of wearable sensors and the anti-adhesion of electrical knives and electrocoagulation hooks. These bring up the common requirements of bio-instrument interface, i.e. the strong wet attachment and high-temperature anti-adhesion properties. Here, inspired by nature, we have studied the tree frog’s toe pad (strong wet crawling) and Nepenthes alata peristome (ultra wet slippery at the oral edge) and extracted their material properties and microstructure characteristics. Their interfacial liquid adjusting rules have been revealed with the coupling effect of surface structure and materials, and the mechanism of strong wet friction and ultra-wet slippery have been established. Bioinspired strong wet friction surface and ultra-wet slipper surface have been designed and fabricated by combining the micro-nano fabrication processes, such as self-assembly and microstructure transfer etching. Finally, by applying bioinspired surfaces onto precision medical devices, and the tolerability of interfacial liquid volume of the bioinspired wearable sensor has been improved ~5 times compare to smooth surface, and the tissue adhesion on bioinspired surgical electrocoagulation is reduced by ~55%.

The local coarse and clear grain defects are found in the TA15 titanium alloy die forging formed in the dual phase region. The metallographic stitching technology and point by point statistical method are used to analyze the macrostructure and microstructure of different macro-grain regions. It is found that the microstructure of clear grain region and fuzzy grain region are typical duplex microstructure of the titanium alloy. Compared with the fuzzy grain region, the content of primary equiaxes α phase (α_P) in clear grain region is slightly lower, and the lamellar thickness of secondary α phase is slightly thicker, but there are a lot of coarse original β grains, whose average size is more than 3 times of that of fuzzy-grained region. According to papers, the coarse original β grains are the main factors leading to clear grain defects. The critical condition of clear grain on the surface of the forging is proposed. The same batch of original material is used to perform hot compression tests. The evolvement law variation of macrostructure and microstructure are obtained under different deformation processes. The prediction model of the original β grain size of TA15 titanium alloy is established, so the visualization prediction of macrostructure is realized. The results show that the dynamic transformation can lead to the coarsening of β grain and the clear grain of macrostructure. The clear grain is sensitive to temperature, deformation and strain rate. When other conditions are constant, the higher the deformation temperature, the larger the deformation amount and the smaller the strain rate, the higher the tendency of macrostructure to be clear grain.

Using a pin-on-disc testing rig and a temperature-controlled chamber to simulate the braking behavior of train in low temperature environment. The influences of braking pressure and speed on the friction and wear performances of the brake disc and brake pad in low temperature environment (-20 ℃) are studied. The results show that the friction coefficient and wear rate of the brake disc and the brake pad at low temperature (-20 ℃) are slightly higher than those at the room temperature (20 ℃). In low temperature environment, braking pressure and braking speed have obvious influences on friction, wear and damage behaviors of brake materials. With the increase in brake pressure, the friction coefficient between the brake disc and the brake pad decreased firstly and then tended to be stable. With the increase in brake speed, the friction coefficient decreased firstly and then increased. With the increase in brake pressure, the wear rate of brake disc and brake pad increased firstly and then tended to be stable, and the wear rate of brake pad material was greater than that of brake disc material. With the increase in brake speed, the wear rate of brake disc decreased rapidly, while the wear rate of brake pad decreased firstly and then tended to be stable. With the increase in braking pressure and braking speed, the third body layer on the worn surface of the brake pad was more evenly distributed, and the number and area of peeling pits on the surface showed a decreasing trends.

Artificial muscle usually refers to a flexible material or device that can perform movements such as extension, expansion, bending, and twisting under external physical or chemical stimulation and do work to external object. The artificial muscle can greatly improve the robot's flexibility and adaptability, and human-machine interaction. The development of artificial muscles has a history of more than sixty years, and the methods to stimulate them are also various, such as by electricity, by heat, by internal pressure, etc. This research attempts to give a review of artifical muscles in driving principle, performances, applications and development trends, with a view to provide references and comparisons for roboticists and other researchers who are interesting in it.

Machine tool intelligent control system, as an integral part of future intelligent machine tools, plays a significant role in improving core competencies of manufacture. Compared with traditional CNC system, the intelligent one has the advantage of higher efficiency and more stable manufacturing quality. It’s able to make intelligent decisions and substitute experiences of human operators. Considering that there are few reviews on intelligent control system of machine tools, the framework and architecture of the machine tool intelligent control system is proposed by analyzing features from four stages of historical development of the machine tool control system. From the perspective of advanced technology, the related key technologies and engineering applications are elaborated, such as artificial intelligence, digital twins and cloud services. At last, after analyzing several major challenges of intelligent machine tools and their countermeasures, the future development trend of machine tool intelligent control system is forecasted.

Multiple 3-R(SRS)RP multi-loop mechanisms are used as modules to integrate a manipulator for obtaining high rigidity, high intensity, high mobility, and large workspace, thereby satisfying the requirements of space on-orbit tasks. Based on the configuration of the multi-loop mechanism, a whole structure design scheme of the space manipulator, including structural designs of SRS compound hinge, multi-loop mechanism module, and multi-loop mechanism system, is proposed. The SRS compound hinge is designed on the basis of an improved spherical joint mechanism. Two spherical and one additional revolute joints are combined, and all the motion axes intersect at one point, thereby improving the motion accuracy and simplifying kinematics model. Then, one connection method between platforms of different modules is developed for constructing the space manipulator system. Each module of the system is designed by planning its connecting links. Thus, the axes of the revolute joints on moving and base platforms are coincident, thereby meeting the requirements of folding and bending motion process. This design strategy eliminates the structural interference of coupling kinematic chains. In addition, the inverse-kinematics models of the multi-loop mechanism module and system are established thus inverse-kinematics analyzing. Based on the kinematics model and analysis, the numerical analysis of the workspace of multi-modular manipulators is conducted. It turns out that the three-modular manipulator achieves a large reachable workspace and bending angle, which provides theoretical basis for manufacture of the prototype.

It is one of the frontier research directions of intelligent manufacturing to use robots as manufacturing equipment executor integrating intelligent vision sensors to realize small margin grinding/milling/cutting/drilling for large and complex parts. At present, the main problem confronting in application is that the machining error is hard to reduce. The study systematically investigates the geometric error modeling and accuracy control of visually-guided robotic machining, where the machining error reduction is regarded as the main objective and the robot/visual sensor/workpiece/tool are regarded as the main targets. The first I part introduces the research status of geometric error modeling and parameter identification, studies the spatial motion chain and metric index definition of robotic machining, and derives the static error (originating from workpiece/tool pose error) transmission model as well as dynamic error (originating from joint kinematic error and joint weak stiffness) transmission model. The second II part builds the objective function and calculation method of accurate identification for hand-eye/workpiece/tool pose parameters, and proposes a general pose optimization model of robotic machining (grinding/milling/cutting/drilling) for overall error control, where the joint kinematic error and weak stiffness deformation are both considered.

Aiming at the lack of recognition of inclined parking spaces in automatic parking system, a method of intelligent recognition of inclined parking spaces in daily life is proposed, and multi-condition parking spaces recognition and parking are achieved. Based on the recognition of existing parallel and vertical parking spaces, the method is combined with distance and visual information. In this method, the information of ultrasonic sensor, camera and wheel speed sensor are used to obtain the pose feature parameters of a vehicle, the Sugeno fuzzy inference method is used to to determine three different types of parking spaces: horizontal, vertical and inclined. subsequently, the multi- condition parking space identification model and the corresponding path planning model are built in Matlab/Simulink soft, and the simulation is carried out for six different types of inclined parking spaces, parallel parking spaces and vertical parking spaces. finally, the real vehicle test is carried out. The simulation and real vehicle test results show the effectiveness and rationality of the above parking space identification method and path planning strategy.

The recovery and remanufacturing of end-of-life (EOL) products can not only realize the recycling of product resources and promote the development of circular economy, but also play a role in energy saving and emission reduction. From the perspective of the product life cycle, energy consumption generated is focused during each step/stage of the product manufacturing process and the optimization of energy consumption in the selective disassembly planning (SDP) is studied during the product manufacturing process. The decisions of disassembly level, disassembly sequence, and the recovery options of subassemblies are simultaneous made in our problem to identify the optimal disassembly solution that maximizes economic and energy-saving benefits from the recovery of EOL products. First, based on the basic mathematical model of SDP and embodied energy of the product manufacturing process, an energy consumption optimization model for SDP is established, considering two evaluation indicators (objectives) i.e. the maximum of profit generated and energy consumption saved from the recovery of EOL products. Then, an improved artificial bee colony algorithm (IABC) is proposed to efficiently solve the energy consumption optimization model of SDP and obtain a comprehensive disassembly solution with large recovering profit and good energy-saving benefit. Finally, a real case for recovering a used LCD television is applied to verify the feasibility and effectiveness of the proposed model and algorithm. The computational results show that the balance of the energy consumption optimization model of SDP is significantly better than the basic mathematical model of SDP, and IABC performs excellent in terms of the convergence, robustness, and computational efficiency.

Health condition monitoring of machinery has entered into the big data era，which brings new opportunities to machinery fault diagnosis. However，due to the abnormal operating environment，disturbance from human and fault data acquisition devices，condition-monitoring data generally include lots of data with abnormal or missing values，which reduces the quality of data seriously. Wrong diagnosis results are probably obtained from the analysis of the low-quality data，leading to inappropriate strategy of machinery maintenance. To solve this problem，a condition-monitoring vibration data recovery method is proposed based on tensor decomposition. A four-order tensor including rotational speed，time-domain window，multi-scale using wavelet transform，and time is constructed. Tucker decomposition is used to process this four-order tensor for extracting the information of health condition and missing data are recovered by tensor completion. Simulated data and real vibration data are used to verify the effectiveness of the proposed method，respectively. The result shows that the data recovered by the proposed method are more close to the real data，compared with traditional data recovery methods，which demonstrates its effectiveness for data recovery in data quality assurance. The proposed method is applied to improve the quality of the condition-monitoring data collected from wind power equipment.

Four-wheel independently driving electric vehicles are one of the most promising electric vehicle schemes. Because the wheel motor is driven independently, the operability of system is improved, and the energy consumption generated by the tire can be independently controlled, which provides development potential for control on automobile energy-saving. An accurate model on the tire longitudinal and lateral energy consumption of four-wheel independently driving electric vehicle is the key point while it is the theorical basis for energy saving control. At present, research on the energy consumption models of tire longitudinal and lateral slip, and research on the energy consumption modeling of four-wheel independently driving electric vehicles need to be further improved. Based on the longitudinal and lateral energy consumption characteristics of four-wheel independently driving electric vehicle tires, the energy consumption mechanism of four-wheel independently driving electric vehicles is analyzed. Firstly, the longitudinal and lateral energy consumption models of the tires are developed. And then based on the slip energy consumption model and the electric vehicle energy consumption characteristics, an improved vehicle energy consumption model is introduced. Secondly, in the Carsim / Simulink joint simulation environment, a four-wheel independently driving electric vehicle model and energy consumption model are built, which provides an accurate and reliable simulation platform for the energy consumption research of four-wheel independently driving electric vehicles. Finally, simulation results under different working conditions prove the necessity of energy optimization control considering the energy consumption of lateral slip.

Knee-postoperative rehabilitation training robot (rehabilitation training robot in short) is developed to assists patients who undergoing knee surgery for rehabilitation training, help them recover knee-joint's function and reduce the workload of rehabilitation physiotherapists and families, which is widely used in rehabilitation training after knee surgery. The movement characteristics of knee joint and rehabilitation needs after operation are first summarized, and then the rehabilitation training robots are classified into three types (i.e., end-effector, exoskeleton, and other types). The design concept, structural characteristics, control strategies of rehabilitation training robot, and rating system of rehabilitation training effect are also addressed in detail. The existing problems, key technologies, and development trend of the knee rehabilitation training robot are concluded and discussed.

Data and knowledge are the basis for the deep integration of new-generation information technology and intelligent manufacturing. However, the storage of data and knowledge in the processes of product design, manufacturing, assembly and service is mostly based on relational database, which brings data redundancy and inefficiency of searching and reasoning. Recently, knowledge graph technology, based on the idea of semantic network, has developed rapidly. It can achieve the description of real-world things and their relationships, which provides a mean for the correlation representation of data and knowledge, and a solution of the relevance searching and reasoning problem in the area of intelligent manufacturing. Therefore, it plays an increasingly important role in the realization of intelligent manufacturing. In order to provide the theoretical support for the application of knowledge graph, a review about the research status of knowledge graph is provided. At the same time, three major applications of knowledge graph in the area of intelligent manufacturing are explored, including a total of 15 small application prospects. Among them, the differences compared with traditional methods, the knowledge graph technology to be introduced and the key technologies to be breakthrough are detailed. It is hoped that it can provide inspiration for researchers to further carry out study on the knowledge graph in the area of intelligent manufacturing, and provide reference for mechanical companies on the application of knowledge graph. Finally, a case about the lathe failure analysis is used to verify the superiority of the knowledge graph in the area of intelligent manufacturing.

In the disaster scenes, such as earthquake and fire, the urgency of the rescue mission highlights the urgent need for intelligent emergency rescue equipment. The use of intelligent emergency rescue equipment can greatly improve the combat effectiveness of the rescue team, and deal with various disasters quickly and efficiently, especially the sudden and serious disasters. It can reduce the casualties and property losses, which is of great significance for its research. According to the working environment and use, intelligent emergency rescue equipment can be divided into air, land, underwater and common rescue equipment. On the basis of summarizing the research status of intelligent emergency rescue equipment and key technologies, it is found that there are still some problems in the current research, such as lack of efficient mechanism design method, poor reliability of equipment, low intelligence, low maturity of communication technology and poor man-machine friendliness, which lead to the low application of intelligent emergency rescue equipment in large-scale disaster field. Intelligent emergency rescue equipment will develop in the direction of advanced structure design, reliable motion performance, high intelligence, fast and accurate communication and good human-computer interaction.