In order to meet the requirements of unmanned underwater vehicle (UUV) launching the torpedos,a new underwater ejection scheme with flexible piston rod is proposed.In the ejection scheme,the high pressure in large depth environment is used to drive the piston to launch a torpedo.An interior trajectory calculation model of torpedo launched from the ejection device with flexible piston rod is established.And the model is verified by the principle test in the high pressure water tank laboratory.The different launching schemes in the related literatures are comparatively studied based on the model.The results show that the ejection scheme with flexible piston rod has the characteristics of smooth acceleration without steep change,large effective acceleration stroke and high pipe exit speed compared with the traditional multistage cylinder launching scheme.Compared with the traditional high-pressure gas-driven piston scheme,the high-pressure water-driven piston scheme is simpler in structure without pressure storage device.A piston buffer scheme based on load reduction in steps proposed in the paper has better load reduction effect compared with the traditional throttle hole buffer scheme.And it won’t cause excessive pressure in the reverse cavity of piston cylinder.Under the ambient pressure of 1.1-6.1MPa,the predicted velocity of torpedo exiting tube varies from 7.0 to 11.6m/s,and the rear reference point of torpedo dose not collide with the tube wall.The results verify the feasibility of the underwater ejection scheme with flexible piston rod,which provides the design basis for the further development of ejection device.

Stable and high-precision localization is a prerequisite for realizing the cooperative autonomous navigation of unmanned ground vehicle (UGV).LiDAR simultaneous localization and mapping (SLAM) often fails to achieve the precise localization in scenarios lacking geometric features,such as corridors,tunnels,and deserts.Therefore,a leapfrog cooperative LiDAR SLAM degradation correction method is proposed for UGVs.This method is used to estimate the normal vector of each feature point in the current frame,and a LiDAR SLAM degradation detection algorithm is devised.When the degradation of environment is detected,the ranging information about two unmanned vehicles is utilized to correct the degradation in LiDAR SLAM.Finally,the locating results are further optimized in the pose graph.Testing on two self-built UGV platforms reveals that the proposed method achieves better mapping performance compared to the current famous LiDAR SLAM methods,demonstrating its significant capability to enhance the locating performance of LiDAR SLAM in degraded scenarios.

This paper investigates the trajectory planning issue for fixed-wing UAVs and proposes a real-time trajectory planning method based on exact convex relaxation.This method includes two steps,i.e.path planning and velocity optimization.In the first step,a flight path of UAV in the multi-obstacle environments is designed.In consideration of the dynamics and control constraints,an obstacle avoidance path planning method based on Dubins path is proposed to generate a flyable obstacle avoidance trajectory.In the second step,the velocity and control of a fixed-wing UAV flying along an obstacle avoidance path are calculated such that it can track the obstacle avoidance path.The nonlinearity retention and exact convex relaxation are used to convert the highly nonlinear velocity optimization problem into one single convex optimization problem,and the validity of the proposed method is theoretically proven.Since there is no iterative process of solving the convex optimization problems,the velocity optimization algorithm does not have convergence issues and has remarkable real-time performance.The simulated results demonstrate that the proposed method can realize obstacle avoidance trajectory planning reliably and rapidly in both multi-obstacle environment and unknown obstacle environment,and it significantly improves the computing efficiency compared with the nonlinear programming and successive convex optimization methods.The calculation time is only tens of milliseconds.

With the rapid development of unmanned aerial vehicle (UAV)-related technologies,the intelligent UAV swarms have attracted more and more research attention.The organizational algorithm models of natural swarms are used for the intelligent UAV swarms,and combined with other intelligent technologies to form advanced group intelligence behaviors,which have the advantages that traditional single artificial intelligent agents cannot match.However,the issue of reliability is also an important factor that restricts its large-scale application.The concept,characteristics,and technological development path of intelligent UAV swarms are systematically analyzed.Based on the application scenarios,application modes,and behavioral processes of intelligent UAV swarms,the connotation of UAV swarm reliability is discussed.A technological framework for the reliability of UAV swarms is constructed,and the technical approaches and suggestions for the development of UAV swarm reliability technology are given based on the technological characteristics and application requirements of intelligent UAV swarms.Under the reliability connotation of “one core, two capabilities, and N foundations,” a reliability technology framework for intelligent UAVs has been proposed,which consists of reliability metrics,reliability development and verification,and reliability maintenance and support technologies.

In order to study the effect of horizontal inflow on the aerodynamic characteristics of small unmanned aerial vehicle (UAV) rotors,the wind tunnel test and numerical simulation are conducted to obtain the multi-dimensional aerodynamic data and wake vortex diffusion characteristics of UAV rotors under different inflow speeds.A low-speed wind tunnel is used to simulate horizontal inflow,and a six-component force-moment sensor is used to measure the aerodynamic forces the rotational speeds from 2000r/min to 9000r/min.The experimental study focuses on analyzing the variations of lateral force,and pitch and roll moments in the rotational plane.The influence of inflow speed on surface pressure distribution during the rotational period and the morphological characteristics of the near-field wake vortex are discussed from the numerically simulated results.The results indicate that the optimal rotational speed range of rotor is 4000-6000r/min under the action of horizontal inflow The x-axis force in the rotational plane is the primary contributor to the lateral force,with both x-axis and y-axis moments playing roles simultaneously.The lateral forces and moments become significant at inflow speeds above 5m/s and must be considered in dynamic analysis.The horizontal inflow disrupts the symmetrical feature of the rotor wake vortex.The inflow with greater speed leads to a larger inclination angle,causing the diffusion evolution of wake vortex to be compressed.

Chaff centroid jamming of unmanned platform is an important means of missile terminal defense.The intelligent decision-making ability in platform maneuvering and chaff launching is an important factor to determine whether the strategic assets can be protected successfully.The current decision-making methods,such as computational analysis based on mechanism model and space exploration based on heuristic algorithm,have the problems of low degree of intelligence,poor adaptability and slow decision-making speed.A dynamic decision-making method of chaff jamming for terminal defense based on multi-agent deep reinforcement learning is proposed.The problem of cooperative chaff jamming of multi-platform for terminal defense is defined,and a simulation environment is constructed.The missile guidance and fuze model,unmanned jamming platform maneuvering model,chaff diffusion model and centroid jamming model are established.The centroid jamming decision problem is transformed into a Markov decision problem,a decision-making agent is constructed,the state and action spaces are defined,and a reward function is set.The decision-making agent is trained by using the multi-agent proximal policy optimization (MAPPO) algorithm.The simulated results show that the proposed method reduces the training time by 85.5% and increases the success rate of asset protection by 3.84 compared with the multi-agent deep deterministic policy gradient (MADDPG) algorithm.Compared with the GA,it reduces the deciding time by 99.96 % and increases the success rate of asset protection 1.12.

In order to improve the design ability of modified double base(MDB)propellant formulations, different intelligent algorithms were used for the formulation design and optimization of the burning rate property. By comparing several typical intelligent algorithms, including genetic algorithm(GA), differential evolution algorithm(DE), particle swarm optimization algorithm(PSO)and whale optimization algorithm(WOA), the intelligent formulation design and optimization of MDB propellants containing RDX were carried out. The results reveal that compared to the statistical optimization method, the intelligent optimization algorithm is simple to be operated and runs more quickly, while the 14 optimal formulations fitted by differential evolution algorithm have the best and more stable burning rate performance. Under the same pressures, the predicted burning rates of these 14 optimized formulations are significantly higher than the experimental values of the prepared formulations. Finally, a set of intelligent algorithm software for predicting the burning rate of modified double base propellants containing RDX is formed by coupling the difference algorithm with the support vector regression model. Based on the intelligent algorithm software, new formulations with the superior burning rate property could be deduced.

Object tracking is an important part of UAV visual guidance,and the tracking accuracy determines the combat effectiveness of UAVs on the battlefield.There are many problems with general object tracking in UAV guidance:fast scale change,large appearance change,slow inference speed and lack of dataset.In order to solve the problems,this paper proposes Guidance-Tracker,an adaptive UAV siamese tracker for visual guidance.The adaptive search region mechanism adjusts the search region to fit the fast scale change by analyzing the guidance process,and the adaptive template updating mechanism updates the template feature to fit large appearance change.Besides,FasterNet Block and anchor-free mechanism are respectively introduced in the backbone network and the tracking head to speed up the inference time.In addition,an object tracking test dataset Guidance UAV for visual guidance,which contains 12 videos, is constructed to evaluate the performance of trackers in visual guidance.The experiment results indicate that Guidance-Tracker is not only suitable for use on the general UAV tracking dataset UAV123,but also achieves state-of-the-art performance on the Guidance UAV,while maintaining a speed of 15f/s on the onboard device Jetson Xavier NX.The indoor guidance experiments shows the effectiveness of the Guidance Tracker.

To improve the combat effectiveness of multi-UAVs cooperative air-to-ground attack task and the efficiency of cooperative task assignment,a task assignment method based on the result of combat unit damage probability is proposed.Three kinds of typical ground target damage eveluation models are established,and the damage probability of each target under different strike directions,as the data support for task assignment,is calculated.In view of the typical scenario of each UAV carrying different weapons to strike ther ground targets,an improved hybrid particle swarm optimization algorithm is proposed to solve the task assignment problem.The crossover and mutation operations of genetic algorithm are used to update particle positions.The crossover operation and mutation operation are improved,and the particle inversion operation is introduced to increase the diversity of particles and avoid falling into local optimum.The proposed method is verified by simulation examples.The simulated results demonstrate that,after using the damage assessment model to calculate the damage probability of ground targets,the proposed method can be used to obtain a task assignment scheme that meets the constraint conditions while meeting the damage requirements,and improve the overall combat effectiveness of the multi-UAV system.

A SBE_YOLOv8s small target detection algorithm based on multi-scale attention mechanism is proposed for the UAV aerial images with high density,small target size and complex background.First,a feature extraction module EF_C2f(EMA-Faster Block_C2f) based on the multi-scale attention mechanism is designed to replace the C2f module in the YOLOv8 network to improve the network’s ability to extract small target features.And then a P1 detection layer is added to the feature fusion network,and a cross-scale feature fusion structure BPAN(Bi-Path Aggregation Network) is designed to fuse the small target feature information.Finally,a tiny target detection head is added,and SIoU Loss is used as the bounding-box loss function to improve the detection accuracy of small targets and the convergence speed of the network.The proposed algorithm is validated on the public dataset VisDrone2019.Compared with YOLOv8s algorithm,the proposed algorithm improves the detection accuracy by 6.9% and mAP₅₀ by 9.1%,and reduces the amount of parameters of the model is by 46.4%,and the detection speed is 28 fps.The experimental results show that the proposed algorithm has a certain degree of utility in the field of small target detection.

In order to study the quantitative structure-property relationship(QSPR)between the detonation performance of pyrimidine energetic compound and its molecular structure, a novel structure index, namely, positioning correction index B, was derived based on the spatial characteristics of atomic interconnections in pyrimidine energetic compound molecules. Moreover, the electrical topology state indexes of 19 energetic compound molecules were calculated, and the electrical topology state index E₁₃ was selected as the structural descriptor. The electrical topology state index E₁₃ was combined with positioning correction index B, which was introduced to the regression analysis of the detonation performance of pyrimidine energetic compound. The neural network models predicting the detonation performance of pyrimidine energetic compound were constructed, where the structural indexes B and E₁₃ were used as the input variables of BP neural network, and 2-3-1 as the network structure. The results show that total correlation coefficient for each model is more than 0.99, which means the excellent level of correlation. The average relative errors between the predicted values and the literature values of oxygen balance(OB), detonation heat(Q), detonation velocity(D)and detonation pressure(P)are 1.59%, 1.05%, 0.37% and 1.28%, respectively. Satisfactory results can also be obtained when introducing the index to analyze and predict the detonation performance of oxtriazole fused ring energetic material molecules and fluorinated azole energetic compound molecules. It is proved the there is a good non-linear relationship between the positioning correction index, electrical topology state index and the detonation performance of pyrimidine-based energetic material molecules.

Ballistics is one of the foundational disciplines in weapons science and technology,closely related to the development of weapons technology. With the rise and development of intelligent projectiles and rockets,the theory and technology of intelligent ballistics will be a major direction for the future development of exterior ballistics. Nevertheless,how to understand the concept,connotation,and functions of intelligent ballistics,as well as its differences from existing projectiles and rockets in terms of flight trajectories,the key technologies it relies on,the challenges involved,and the issues that should be considered for the subsequent development,are still under discussion. Based on the theory and technology of exterior ballistics and focusing on the future development of exterior ballistics,this article tends to analyze and organize the aforementioned issues with the aim of providing assistance for the future development of intelligent ballistics theory and technology. It should be noted that the development of intelligent ballistics theory and technology has introduced numerous new problems,concepts,terminologies and technologies for exterior ballistics,which require continuous exploration,refinement,and gradual perfection by researchers in the field of exterior ballistics through ongoing research. This article merely serves as a starting point,hoping to inspire more researchers in the field of exterior ballistics to engage in this area of study and gradually develop a theoretical framework.

Cross-domain collaborative mission planning is the key technology and important support for the clustering, autonomization and multifunctionalization of unmanned systems. Focusing on ocean autonomous unmanned system, the basic concept, principle and characteristics of unmanned system cooperative mission planning are expounded, and the typical application cases of unmanned system cooperative mission planning are analyzed. The basic process and control structure of unmanned system cooperative mission planning are presented. A distributed mission planning model is constructed. The future research prospects are summarized by analyzing the existing problems in order to provide some reference for the construction and development of ocean autonomous unmanned system.

The unmanned systems are difficult to perform a mission in complex scenarios.The consensus models and collaborative control methods for large-scale unmanned cluster are studied by taking the emergence of swarm intelligence as the starting point of the research and the quadrotor drones as the research object.A neighbor selection mechanism and an adaptive attraction and mutual repulsion mechanism for the spatial partitioning of perception perspective are designed to generate the cluster spatial configuration.Combining the formation mechanism of social consensus in opinion dynamics,a view synthesis mechanism is constructed to achieve cluster speed synchronization.The autonomous group separation and aggregation rules are proposed and an obstacle avoidance method that combines active avoidance and safe strategy are proposed,so that the cluster size is flexibly adjusted to adapt to the dense obstacle environments.Simulated results show that the proposed method can be applied to a distributed cluster of 50 UAVs.In indoor,forest and urban environments with multiple obstacles,a cluster of 10 drones can safely cross an obstacle zone at a flight speed of 5m/s.The proposed method can be also applied to a distributed cluster of 4 UAVs which can safely traverse indoor obstacle zones,verifying the effectiveness of the cluster model.

As the potential applications and strategic value of unmanned ground vehicles(UGVs)in complex operational environments become increasingly prominent,the safety of their autonomous actions is of paramount importance.This paper proposes a system safety analysis method for UGV,which combines the system-theoretic process analysis(STPA)method and the Bow-Tie model.Focusing on the safety of teleoperated UGVs,the STPA method is utilized to identify the unsafe control actions(UCAs)within the UGV system and their associated latent risks.Subsequently,the Bow-Tie model is utilized to analyze the event chain from loss causation scenarios to potential accident consequences,thereby delineating the risk propagation and diffusion pathways.Ultimately,the active and passive safety stratified control measures are determined based on the Bow-Tie analysis,and the system safety management is realized through an autonomous safety controller.

The judgement of drone swarm attack intent involves many fuzzy and uncertain factors,and the judgement process belongs to the uncertainty reasoning process.A judging method based on discrete dynamic Bayesian network model is proposed for the judgement of drone swarm attack intent.According to the characteristics of drone swarm use,an indicator system for the determination of drone swarm attack intent is constructed.The continuous variables in the indicator system are transformed into the discrete variables by using fuzzy logic theory,and a model for drone swarm attack intent determination method is established.To address the problem of missing the indicator data in the evaluation process,a forward information repairing algorithm is used for information prediction and repairing.The simulated results show that the proposed method has a certain degree of fault tolerance,and can effectively judge the attack intent of drone swarm target based on the information before and after repairing,providing a reference for anti-drone swarm combat command decision-making.

Aiming at the reconnaissance task allocation of air-ground heterogeneous unmanned system,this paper proposes a two-stage mixed task assignment(TMTA)algorithm for reconnaissance tasks and communication relay tasks.An alternative set of reconnaissance position and communication relay position are constructed based on the reconnaissance distance,communication relay distance and target position.An reconnaissance and communication relay tasks dispatching model is built by taking the task timeliness and path cost as the objective functions,in which the combining reconnaissance/communication relay task completion constraints,coupling constraints between task location selection/task execution time and task paths,and path continuity constraints,etc.,are considered.To solve the nonlinearity of the model,the advantages of set coverage algorithm,Hungarian algorithm,and genetic algorithm are synthesized to design a TMTA algorithm,which realizes the efficient solution of the model.The proposed method is validated through experiment.The experimental results show that the proposed algorithm outperforms the baseline dispatching algorithm in terms of task timeliness and path cost.

With the wide application of intelligent collaborative algorithm and autonomous technology in the field of air,space and sea equipment,the multi-domain cluster distributed collaborative autonomous control technology has also been deeply studied,and significantly improved the degree of intelligent autonomy of unmanned equipment.Based on the development needs of distributed intelligent autonomous control technology of multi-domain cluster,this paper reviews the relevant references related to multi-domain cluster distributed intelligent autonomous control technology and the research status at home and abroad.The relevant strategies,key research directions and advanced methods of multi-domain cluster collaborative autonomous control technology are deeply analyzed.The relevant key technologies and methods are summarized,and the future development trend is discussed.This paper provides a reference for improving the collaborative autonomous control ability of unmanned cluster system.

Unmanned surface vehicles (USVs) have high mobility,strong concealment,and extensive operational range,making them highly suitable for performing a wide array of tasks such as reconnaissance,anti-submarine warfare,search and rescue.Environmental perception technology,crucial for the operation of USVs,has attracted considerable attention.This paper conducts a survey on the development status of environmental perception technology for USVs at abroad,and define and analyzed the challenges in USV environmental perception through specific case studies.The current state of research on USV environmental perception technology is analyzed from the perspectives of both unimodal and multimodal perception,considering the sensory equipment utilized by USVs.Finally,the unresolved challenges in USV environmental perception technology are summarized,and its future development is prospected.

In view of the requirements of current solid rocket motor,such as unrepeatable start and stop, difficult to achieve controllable thrust, combined with the advantages of solid rockets and liquid rockets, research institutions at domestic and foreign have explored an electrically controlled solid propellant with repeated ignition and flameout, adjustable combustion speed and controllable output energy. The research status of new electronically controlled solid propellants at home and abroad is systematically introduced. Firstly, the development of various electronically controlled solid propellants(ammonium nitrate, hydroxylamine nitrate, lithium perchlorate)at home and abroad is summarized, as well as their applications in micro-thruster, artillery shell igniters and solid engines. Secondly, the effects of formula composition, voltage, current, external ambient temperature and pressure on the combustion rate, ignition delay time and mechanical properties of electronically controlled solid propellants are summarized. Then, the start-stop mechanism of electronically controlled solid propellant was analyzed, and the reaction mechanism of ammonium hydroxylamine nitrate and lithium perchlorate based electronically controlled solid propellant was introduced. Finally, the future development of electronically controlled solid propellants is prospected, and it is pointed out that there are still key research directions in the future: enhance the research on the preparation process amplification of electronically controlled solid propellants; design new electrosensitive oxidants to solve the problem of uncontrollable combustion under high pressure; carry out experimental research of large-scale electronically controlled solid engines; reveal the coupling effect of electric energy and propellant combustion by numerical simulation. 62 References are attached.

To address the issues of systemic inadequacies, lack of correlation, and insufficient consideration of complexity in the effectiveness evaluation of land-based intelligent unmanned combat systems, a graph convolutional network (GCN)-based effectiveness evaluationframework is proposed. The framework aims to leverage GCN technology to precisely evaluate the performance of intelligent unmanned combat systems. A comprehensive set of evaluation index systemis established according to the characteristics of land-based intelligent combat, and this system is mapped onto a graph network structure, enabling a highly abstract representation of the unmanned combat system in complex operational environments. The big data analytics and expert knowledge areused to preprocess and engineer the initial dataset for optimizing the quality of input data. The hierarchical structure of the evaluation index system and the interrelationships among its components are deeply explored by applying GCN's semi-supervised learning mode, thereby achieving a comprehensive evaluation of the effectiveness of land-based intelligent unmanned combat systems. This evaluation framework addresses numerous issues existingin the current evaluation of these systems, offering a dynamic, systematic, and comprehensive solution that demonstrates the application potential of GCN in the field of military technology.

With the goal of addressing the challenges of real-time observation and localization of high-value military vehicles on the ground, a real-time algorithm for the detection and localization of military vehicles in aerial photography is proposed. An Armed_vehicle dataset for the detection of multi-type and multi-scale military vehicles in an actual combat environment in aerial photography is established. The detection accuracy reaches 85.82% and the detection efficiency is higher by introducing a large kernel attention (LKA）module into the lightweight neural network model YOLOX-Tiny and using the SIoU edge regression function. A monocular visual localization algorithm based on the visible light images from the unmanned aerial vehicles (UAVs) is proposed. The average target localization error is 3.69 m at a flight altitude of 100 meters. It indicates that the proposed algorithm can accurately obtain the geographical location of ground targets and has good comprehensive performance and application prospects.

The soldiers' combat environments and equipment are undergoing unprecedented changes with the evolution of modern warfare and the rapid development of intelligent technologies. Intelligent equipment, such as augmented reality helmets, wearable devices, and remote operation systems, has become the key to enhancing the soldiers' combat effectiveness. However, the integration and use of these technologies also bring new challenges to soldiers, especially in terms of fatigue. Fatigue affects the decision-making ability, reaction time and attention concentration of soldiers, thereby impacting battlefield performance and task execution efficiency. The current state of research on cognitive fatigue is reviewed, and the causes and impacts of cognitive fatigue as well as monitoring technologies and mitigation strategies are explored. Through the analysis of existing literature, this article aims to provide a reference for future research on cognitive fatigue issues arising from the interaction between soldiers and intelligent equipment. It also proposes suggestions for the military training and the design of intelligent equipment to alleviate cognitive fatigue and enhance soldiers' combat capabilities.

In order to meet the real-time three-dimensional path planning requirements of unmanned aerial vehicles (UAVs) in complex environments, the heuristic function of the A^* algorithm is optimized to address the problems of low real-time performance, large amount of calculation and serious memory consumption in the traditional A^* algorithm when performing three-dimensional path planning. The weight value of heuristic function is adjusted and the heuristic function is used as the base for exponential operation, so as to achieve the purpose of improving the search efficiency. The simulated results show that the algorithm time is reduced by 51.69% and the number of searched grids is reduced by 45.5% after adjusting the weight factor of heuristic function. By optimizing the exponential size of the heuristic function, the algorithm time is reduced by 50.56% and the number of searched grids is reduced by 45.5%. This verifies that the improved A^* algorithm can reduce the path search time and path planning cost compared with the traditional A^* algorithm, and improve the path search efficiency.

Ground-based laser systems are limited in their effectiveness due to obstacles and beam divergence. This limitation can be mitigated by using UAV platforms for close-proximity illumination. Nevertheless, the currently available unmanned aerial vehicles (UAVs) often lack the payload capacity to carry the lasers that meet the necessary power requirements, thus limiting the application of laser systems. To tackle this challenge,a UAV-based laser relay redirectional energy transmission device and its corresponding ground part are designed based on the energy transmission mode of using UAV to turn the light path. Different focusing strategies are discussed, and the system efficiency analysis under simulation conditions is given for different focusing strategies, which can explore a new way for laser system turning irradiation and mobile deployment.

A hierarchical multi-agent collaborative decision-making method based on the actor-critic (AC) frameworkis proposed to address the issues of improper task allocation and weak decision consistency in the collaborative decision-making of multiple agents in complex operational environments. The proposed method divides the decision-making process into different levels and utilizes the AC framework to facilitate information exchange and decision coordination among the agents, thereby enhancing thedecision efficiency and combat effectiveness. At the higher level, the top-level agents formulate thetask decisions by decomposing and assigning overall tasks to the lower-level agents. At the lower level, the lower-level agents make action decisions based on subtasks and provide feedback to the higher level. Experimental results demonstrate that the proposed method performs well in various operational simulation scenarios, showcasing its potential to enhance themilitary operational collaborative decision-making capability.

Maritime manned/unmanned collaborative systems play a crucial role in enhancing naval operational effectiveness and represent a significant direction in the development of modern naval equipment. This paper focuses on the development of maritime manned/unmanned collaborative systems, reviews the current developing status and relevant foreign projects, clarifies the main characteristics of the systems, condenses and analyzes the scientific issues and key technologies involved, and ultimately provides a comprehensive survey on the development of maritime manned/unmanned collaborative systems. In the future, intelligence, modularity and sparsity will become the important directions for the development of maritime manned/unmanned collaborative systems. However, due to the contradictions between system autonomy and controllability, the development of intelligence and maritime constraints, and the features of manned/unmanned collaboration and existing collaborative frameworks, the system will also face challenges in scale, diversity, security, and intelligence-related aspects.

The formation keeping, reconfiguration and transformation functions of unmanned ground vehicle (UGV) formation systems are studied A hybrid leader-follower strategy is proposed to reduce the dependence on the leading vehicle and ensure the formation integrity. An independent obstacle avoidance function based on vehicle-to-vehicle (V2V) communication for the following vehicles is developed, and a formation node management system is designed manages the attributes of formation members in real time and supports the human-computer interaction. A dynamic extended trajectory planning method with cubic spline curve in three-dimensional space is proposed to generate the following trajectory and realize the obstacle avoidance by acquiring the position information of the front vehicle through V2V communication. The Frenet coordinate system is utilized to decouple the distance keeping and trajectory tracking problems, and the proportional-integral-differential (PID) controller and linear quadratic regulator (LQR) controller are used for longitudinal control and lateral trajectory tracking, respectively. The research results show that the performance of the proposed method can be quickly verifued in the simulation environment built, showing that the method has good performance. And the three functions of the vehicle formation system are verified by real vehicles, and the proposed method is confirmed to have good real-time performance through the stable maintenance of the distance between the vehicles, which is capable of realizing the effective following of the multi-vehicle formation, and shows a high degree of intelligent expansion and adaptability through the transformation of multiple formation shapes as well as the scenarios of members' joinning and departuring from the vehicle formation.

In order to expand the application scope of folding wing UAV and extend the information acquisition ability of underwater platform,an underwater vehicle scheme of carrying UAV for dry launch was proposed by combining the advantages of UUV and UAV. In order to better evaluate the feasibility of launching UAV on the sea,the computational fluid dynamics simulation software StarCCM+ was used to simulate the launching environment of UAV on the sea,and the floating and launching process of UAV was simulated in the simulation environment. The air-bag scheme and the propeller scheme were designed respectively by referencing foreign design experience,and the different sea-conditions,different structural-parameters and attitude parameters were simulated and evaluated,and finally the launching process was simulated under the sea conditions. The results show that the UAV carrier in the state of zero buoyancy underwater can float stably on the water surface under different sea-conditions by the air bag scheme and the propeller propulsion scheme. In terms of UAV launch,the difference between the maximum sinking distance of the air-bag scheme in still water and sea conditions is about 2.5%,and the consistency is better than the error level of the propeller scheme of 30%. The average maximum sinking-distance of the vehicle during the launch of UAV is 0.28 m,which is lower than 0.4 m of the propeller propulsion scheme. In a comprehensive comparison,the air-bag scheme is more stable and reliable.

In order to overcome the question of large fluctuation of trajectory tracking accuracy due to complex external unknown interference in the trajectory tracking control process of six-freedom-degree quad-rotor UAV,a new-type cascaded double-closed-loop control strategy was proposed for velocity error,and position and attitude error. Firstly,the model predictive control(MPC)was used to project the velocity closed-loop controller,and the sparrow search algorithm(SSA)was applied to the rolling optimization process of MPC to obtain the feasible solution due to the fast convergence and strong robustness. In order to solve the large computation in MPC,sliding mode control(SMC)was used to design the dynamic controller according to position and attitude respectively. SMC is insensitive to external interference,robust and does not need accurate modeling,thus solving the problems of external uncertain interference and difficulty in accurately modeling UAV. The saturation function was used to replace the symbolic function to make the input of the actual system continuous,thus effectively reducing the high-frequency chattering phenomenon in SMC. Finally,the stability of the SSA-MPC controller was proved by Lyapunov stability theory. By the proposed method,the six-freedom-degree quad-rotor UAV can achieve high-precision trajectory tracking control under complex external unknown interference and uncertain parameters,and the trajectory tracking accuracy is obviously better than the UAV control system composed of traditional single controller. The proposed controller is effective for the trajectory tracking control of quad-rotor UAV under complex external unknown interference.

Nitrogen content in nitrocellulose was determined by self-developed fully automatic nitrogen determination analyzer. The effects of sample pretreatment conditions and experimental parameters of fully automatic nitrogen determination analyzer on the results were studied. The accuracy and repeatability of test were discussed. Comparison of fully automatic nitrogen determination analyzer method and traditional alloy reduction method was performed. The results show that the sample pretreatment is carried out by graphite oven heating and temperature gradient mode of saponification, the optimum experimental parameters are determined as steam volume fraction of 80%, preheating time of 30s, reduction reaction time of 7min, boric acid solution volume of 35mL, distillation time of 8 min, indicating that the method of nitrogen content in nitrocellulose detected by fully automatic nitrogen determination analyzer is easy to operate with less time,and can ensure the precision and accuracy of the results.

To solve the increasingly serious flight problems of the low-slow-small unmanned aerial vehicle(UAV),an anti-UAV capture gun was designed by the high-low pressure launching theory. The coupled interior and external ballistic model of the anti-UAV capture gun was established. The effects of different charge weights and volumes of high-pressure chamber on the performance of launching device capturing UAV were discussed. The launching performance,portability and safety of the device were investigated by the normalized function of the muzzle velocity,the volume and mass of the device,and the peak pressure of the high-pressure chamber. The launching performance,portability and safety for different conditions were analyzed. The particle swarm optimization was used to improve the capture performance,portability and safety of the anti-UAV capture gun. The study provides a theoretical guidance for the in-depth study of anti-drone capture system.

Aiming at the perturbation of aerodynamic parameters in the waypoint control of unmanned aerial vehicle(UAV),a robust control law against the perturbation of the aerodynamic parameters was proposed,and it was applied for tracking waypoint of a fixed-wing UAV. The effect of the perturbation of the aerodynamic parameters on the traditional control method was analyzed,and the kinematic model containing error term was given. A new control law added with the upper-limit item of the perturbation of the aerodynamic parameters was designed,which enabled the system to be stable. The proposed method was verified by setting a series of large perturbation of the parameters. The result shows that it can guarantee the control precision to introduce the perturbation of aerodynamic parameters.

Taking a small four-rotor UAV with multi-tube launcher as the research object,in order to study the influence of hovering launch of special ammunition on the flight stability of four-rotor UAV,the interior ballistic model of special ammunition launching was established,and the recoil impulse generated by the launcher launching a special ammunition was calculated by interior ballistic programming. Based on Newton-Euler equation,the six-degree-of-freedom dynamic model of UAV and multi-tube launcher was established. Through Simulink modeling calculation,the attitude and position change data of four-rotor UAV and multi-tube launcher were obtained,and the calculated and experimental results are in good agreement. The research shows that under various launch conditions,the four-rotor UAV controlled by PID controller can safely realize hovering launch of special ammunition. The theoretical threshold of recoil impulse for safe launch of four-rotor UAV in hovering state can be obtained by numerical calculation by changing the recoil impulse of four-rotor UAV fuselage. It provides theoretical and data support for the development of four-rotor UAV and multi-tube launcher.

自动装弹机的性能和工作可靠性直接影响着坦克的总体战斗性能,其故障的判断、查找非常困难。针对人工神经网络和专家系统各自的优缺点,研究了基于神经网络的故障诊断专家系统的理论与方法,将此方法应用于自动装弹机系统的故障诊断之中,结果表明该方法非常有效。

机器人技术是实现战车无人化的一项重要技术。随着机器人技术的不断发展,自主式移动机器人技术应用在装甲车辆上将逐渐成为可能。这涉及到的诸多方面的研究成果有:局部与全局导航方案的研究、基于感知的位置判断、障碍物的检测和避障的新方法以及多传感器信息融合等。阐述了机器人技术在装甲车辆上的应用,介绍了其相关技术,对装甲车无人化的现状及发展进行了概述。

Salt spray environment has an important influence on the tactical and technical performance and operational effectiveness of automatic rifles. However, the influence mechanism of salt spray environment on the motion characteristics and failure of rifle automaton is still unclear. A small caliber automatic rifle is taken as the test object，and a life-test in salt spray environment is designed and carried out. A series of measurements and records are carried out on the rifle after each salt spray test, including non-contact measurement of automaton motion by high-speed photography, high precision measurement of the mass of rifle bolt , recoil spring parameters test, and photographic record of bolt box and guide rail surface morphology characteristics. The conditions of failure during the life-test are counted to obtain the typical fault patterns of automaton movement. The results show that the mass of rifle bolt increases gradually with the increase in salt spray test time. The free length and pre-pressure of the recoil spring gradually decrease, and the working pressure tends to be flat after decreasing. The speed at which the bolt carrier recoils to position decreases first and then increases. The speeds at which the bolt begins to return and returns to the original position decrease gradually, and they have the same changing trend. With the decrease of the speed at which the bolt carrier recoils to position, the number of motion faults of the automaton increases, and the multi-parameter changes caused by the salt spray environment have an obvious influence on the automaton motion. Based on the experimental study, the quantitive relation formulas for the changes of the mass of rifle bolt, the recoil spring parameters and the characteristic point velocity with time are built. Quantitive relation formulas provide a reference for inferring the parameter changes of moving parts of automaton in salt spray environment and analyzing their influences on faults in motion.