李昌玺 , 孙玉彪 , 范泽昊 , 等 . 无人作战平台发展现状及趋势 [J ] . 中国电子科学研究院学报 , 2023 , 18 ( 3 ): 274 - 279 .

LI C X , SUN Y B , FAN Z H , et al . Current development and tendency of unmanned combat platform [J ] . Journal of CAEIT , 2023 , 18 ( 3 ): 274 - 279 . (in Chinese)

张哲 , 吴剑 , 代冀阳 , 等 . 基于改进A-Star算法的隐身无人机快速突防航路规划 [J ] . 航空学报 , 2020 , 41 ( 7 ): 254 - 264 .

ZHANG Z , WU J , DAI J Y , et al . Fast penetration route planning of stealth UAV based on improved A-Star algorithm [J ] . Acta Aeronautica et Astronautica Sinica , 2020 , 41 ( 7 ): 254 - 264 . (in Chinese)

王庆禄 , 吴冯国 , 郑成辰 , 等 . 基于优化人工势场法的无人机航迹规划 [J ] . 系统工程与电子技术 , 2023 , 45 ( 5 ): 1461 - 1468 . DOI: 10.12305/j.issn.1001-506X.2023.05.22 http://doi.org/10.12305/j.issn.1001-506X.2023.05.22 针对传统人工势场(traditional artificial potential field，TAPF)法在无人机航迹规划中存在的局部极小值、斥力过大、无效避障等问题，提出一种优化人工势场法。首先将障碍物斥力进行分解，避免了局部极小值情况；其次重构合力计算方式，避免无人机在障碍密集区域所受斥力过大；最后引入二次碰撞预测方法，减少无人机无效避障的同时保证航迹平滑。在考虑无人机物理约束条件下进行航迹规划实验。仿真结果表明，该方法相较于TAPF法，不仅缩短了规划航线长度，且在航迹平滑性上有明显提升。

WANG Q L , WU F G , ZHENG C C , et al . UAV path planning based on optimized artificial potential field method [J ] . Systems Engineering and Electronics , 2023 , 45 ( 5 ): 1461 - 1468 . (in Chinese) DOI: 10.12305/j.issn.1001-506X.2023.05.22 http://doi.org/10.12305/j.issn.1001-506X.2023.05.22 Aiming at the problems of local minimum point, excessive repulsion force, and unnecessary obstacle avoidance in the traditional artificial potential field (TAPF) method in unmanned aerial vehicle path planning, an optimized artificial potential field method is proposed. Firstly, the repulsion force is decomposed to avoid the local minimum point. Then, the calculation method of the resultant force is reconstructed to avoid excessive repulsion force when unmanned aerial vehicle in obstacle-intensive area. Finally, the two-time collision predict method is introduced to reduce the unnecessary obstacle avoidance and ensure a smooth trajectory. The path planning experiments are carried out with considering the physical constraints of unmanned aerial vehicle. Compared with the TAPF method, the proposed method not only shortens the length of planning trajectory, but also significantly improves the smoothness of trajectory.

张飞凯 , 黄永忠 , 李连茂 , 等 . 基于Dijkstra算法的货运索道路径规划方法 [J ] . 山东大学学报(工学版) , 2022 , 52 ( 6 ): 176 - 182 .

ZHANG F K , HUANG Y Z , LI L M , et al . Route planning method of freight ropeway based on Dijkstra algorithm [J ] . Journal of Shandong University(Engineering Science) , 2022 , 52 ( 6 ): 176 - 182 . (in Chinese)

张韬 , 项祺 , 郑婉文 , 等 . 基于改进A * 算法的路径规划在海战兵棋推演中的应用 [J ] . 兵工学报 , 2022 , 43 ( 4 ): 960 - 968 . DOI: 10.12382/bgxb.2021.0209 http://doi.org/10.12382/bgxb.2021.0209 为满足海战兵棋推演中多目标路径规划的需求，解决传统A^*算法无法在兵棋推演中直接运用的问题，提出一种可供类似兵棋推演环境参考、基于改进A^*算法的路径规划方法。建立一种映 射机制，实现了A^*算法在兵棋推演环境中的初步运用。构建一种既能满足多目标需求又能保证生成最优路径的估价函数。为验证算法有效性，在实际推演平台上进行了相关实验。结果表明，改进A^*算法可较好地统筹多个决策目标之间的关系，有效提升路径方案的质量，解决使用A^*算法在海战兵棋推演中进行最优路径规划的实际问题。

ZHANG T , XIANG Q , ZHENG W W , et al . Application of path planning based on improved A * algorithm in war gaming of naval warfare [J ] . Acta Armamentarii , 2022 , 43 ( 4 ): 960 - 968 . (in Chinese)

胡铮 , 徐斌 . 融合A * 算法与人工势场法的动态路径规划 [J ] . 组合机床与自动化加工技术 , 2023 ( 7 ): 46 - 49 .

HU Z , XU B . Dynamic path planning by combining A * algorithm and artificial potential field method [J ] . Modular Machine Tool & Automatic Machining Technology , 2023 ( 7 ): 46 - 49 . (in Chinese)

黄翼虎 , 于亚楠 . 基于改进Dijkstra算法的防冲突最短路径规划研究 [J ] . 计算机与现代化 , 2022 ( 8 ): 20 - 24 .

HUANG Y H , YU Y N . Research on anti-conflict shortest path planning based on improved Dijkstra algorithm [J ] . Computer and Modernization , 2022 ( 8 ): 20 - 24 . (in Chinese)

KENNEDY J . Particle swarm optimization [J ] . Proceedings of ICNN’95-International Conference on Neural Networks , 2011 , 4 ( 8 ): 1942 - 1948 .

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DORIGO M , BIRATTARI M , STUTZLE T . Ant colony optimization [J ] . IEEE Computational Intelligence Magazine , 2006 , 1 ( 4 ): 28 - 39 . DOI: 10.1109/MCI.2006.329691 http://doi.org/10.1109/MCI.2006.329691 http://ieeexplore.ieee.org/document/4129846/ http://ieeexplore.ieee.org/document/4129846/

胡致远 , 王征 , 杨洋 , 等 . 基于人工鱼群-蚁群算法的UUV三维全局路径规划 [J ] . 兵工学报 , 2022 , 43 ( 7 ): 1676 - 1684 . DOI: 10.12382/bgxb.2021.0215 http://doi.org/10.12382/bgxb.2021.0215 针对水下无人航行器在三维环境下的全局路径规划问题，从优化初始信息素分布和转移概率角度，对人工鱼群和蚁群的融合算法进行了深入研究。融合算法中，对人工鱼群算法的状态表达式和移动步长进行了改进；对蚁群算法的启发值、信息素等进行优化设计；借鉴拥挤度因子思想，改进传统蚁群算法转移概率，提升算法的全局寻优能力。在对实际海洋环境数据进行栅格法建模的基础上，以路径长度为衡量指标，利用MATLAB软件进行算法的仿真验证。实验结果表明融合算法的初期收敛速度较快，最佳适应度值和算法耗时均得到改善，算法的有效性得以验证。

HU Z Y , WANG Z , YANG Y , et al . Three-dimensional global path planning for UUV based on artificial fish swarm and ant colony algorithm [J ] . Acta Armamentarii , 2022 , 43 ( 7 ): 1676 - 1684 . (in Chinese) DOI: 10.12382/bgxb.2021.0215 http://doi.org/10.12382/bgxb.2021.0215 To solve the problem of global path planning of underwater unmanned vehicles (UUVs) in a three-dimensional environment, this study examines a fusion algorithm for fish swarm and ant colony that optimizes the initial pheromone distribution and transfer probability of UUVs. The fusion algorithm improves the state expression and moving step of the artificial fish swarm algorithm. The heuristic value and pheromone of the ant colony algorithm are also optimized. Using the congestion factor, the transfer probability of traditional ant colony algorithms is improved, and the new algorithm is capable of global optimization. Based on grid modeling of the actual marine environment data, we take the path length as the measurement index to simulate and verify the algorithm through MATLAB. The experimental results indicate that the initial convergence speed of the fusion algorithm is faster, the optimal fitness value is higher, and the executed time is shortened, verifying the effectiveness of the algorithm.

赵鹏程 , 宋保维 , 毛昭勇 , 等 . 基于改进的复合自适应遗传算法的UUV水下回收路径规划 [J ] . 兵工学报 , 2022 , 43 ( 10 ): 2598 - 2608 .

ZHAO P C , SONG B W , MAO Z Y , et al . Path planning for UUV underwater recovery based on improved composite aaptive genetic algorithm [J ] . Acta Armamentarii , 2022 , 43 ( 10 ): 2598 - 2608 . (in Chinese)

黄鹤 , 吴琨 , 王会峰 , 等 . 基于改进飞蛾扑火算法的无人机低空突防路径规划 [J ] . 中国惯性技术学报 , 2021 , 29 ( 2 ): 256 - 263 .

HUANG H , WU K , WANG H F , et al . Path planning of UAV low altitude penetration based on improved moth-flame optimization [J ] . Journal of Chinese Inertial Technology , 2021 , 29 ( 2 ): 256 - 263 . (in Chinese)

郭威 , 吴凯 , 周悦 , 等 . 基于蚁群算法的深海着陆车路径规划 [J ] . 兵工学报 , 2022 , 43 ( 6 ): 1387 - 1394 . DOI: 10.12382/bgxb.2021.0342 http://doi.org/10.12382/bgxb.2021.0342 针对深海着陆车海底作业“路径最优”问题，提出一种适用于着陆车的三维海底全局路径规划算法。采用栅格等分法建立着陆车作业区域的三维海底环境抽象模型。通过对着陆车航行过程动力学分析和驱动电机速度与工作效率测试，建立其航行运动能耗模型。采用局部和全局信息素更新的基于蚁群寻优的能耗-距离路径规划算法，并将能耗、距离引入到启发函数与评价函数中。仿真实验结果表明，该算法通过合理选取评价函数权重参数，能有效均衡路径规划的里程与能耗，具有较好的收敛速度和全局搜索能力，能够满足深海着陆车海底科考作业需求。

GUO W , WU K , ZHOU Y , et al . Path planning of deep-sea landing vehicle based on ant colony algorithm [J ] . Acta Armamentarii , 2022 , 43 ( 6 ): 1387 - 1394 . (in Chinese) DOI: 10.12382/bgxb.2021.0342 http://doi.org/10.12382/bgxb.2021.0342 A three-dimensional subsea global path planning algorithm suitable for landing vehicles is proposed for “path optimization” of undersea operation of，deep-sea landing vehicles. The grid equal division method is used to establish a 3D submarine environment abstract model for the operating area of landing vehicle. An energy consumption model of navigation movment of landing vehicle is established by dynamically analyzing the navigation process of landing vehicle and testing the speed and work efficiency of driving motor. Local and global pheromone update-based energy consumption-distance path planning algorithm based on ant colony optimization is adopted，and the energy consumption and distance are introduced into heuristic and evaluation functions. The experimental results show that the proposed algorithm can effectively balance the mileage and energy consumption of path planning by reasonably selecting the weight parameters of the evaluation function. It has good convergence speed and global search ability，and can meet the needs of subsea scientific research operation of deep-sea landing vehicle.

SEYYEDABBASI A , KIANI F . Sand cat swarm optimization: a nature-inspired algorithm to solve global optimization problems [J ] . Engineering with Computers , 2022 , 39 ( 4 ): 2627 - 2651 . DOI: 10.1007/s00366-022-01604-x http://doi.org/10.1007/s00366-022-01604-x

KIANI F , FATEME A A , FAHRI E . PSCSO:enhanced sand cat swarm optimization inspired by the political system to solve complex problems [J ] . Advances in Engineering Software , 2023 , 178 : 103423 . DOI: 10.1016/j.advengsoft.2023.103423 http://doi.org/10.1016/j.advengsoft.2023.103423 https://linkinghub.elsevier.com/retrieve/pii/S0965997823000157 https://linkinghub.elsevier.com/retrieve/pii/S0965997823000157

AMIR S . A reinforcement learning-based metaheuristic algorithm for solving global optimization problems [J ] . Advances in Engineering Software , 2023 , 178 : 103411 . DOI: 10.1016/j.advengsoft.2023.103411 http://doi.org/10.1016/j.advengsoft.2023.103411 https://linkinghub.elsevier.com/retrieve/pii/S0965997823000030 https://linkinghub.elsevier.com/retrieve/pii/S0965997823000030

FARZAD K , SAJJAD N , FATEME A A , et al . Chaotic sand cat swarm optimization [J ] . Mathematics , 2023 , 11 ( 10 ): 2340 . DOI: 10.3390/math11102340 http://doi.org/10.3390/math11102340 https://www.mdpi.com/2227-7390/11/10/2340 https://www.mdpi.com/2227-7390/11/10/2340 In this study, a new hybrid metaheuristic algorithm named Chaotic Sand Cat Swarm Optimization (CSCSO) is proposed for constrained and complex optimization problems. This algorithm combines the features of the recently introduced SCSO with the concept of chaos. The basic aim of the proposed algorithm is to integrate the chaos feature of non-recurring locations into SCSO’s core search process to improve global search performance and convergence behavior. Thus, randomness in SCSO can be replaced by a chaotic map due to similar randomness features with better statistical and dynamic properties. In addition to these advantages, low search consistency, local optimum trap, inefficiency search, and low population diversity issues are also provided. In the proposed CSCSO, several chaotic maps are implemented for more efficient behavior in the exploration and exploitation phases. Experiments are conducted on a wide variety of well-known test functions to increase the reliability of the results, as well as real-world problems. In this study, the proposed algorithm was applied to a total of 39 functions and multidisciplinary problems. It found 76.3% better responses compared to a best-developed SCSO variant and other chaotic-based metaheuristics tested. This extensive experiment indicates that the CSCSO algorithm excels in providing acceptable results.

董惠敏 , 安海鹏 , 张楚 . 基于栅格法的人字齿有限元接触精确建模方法 [J ] . 华中科技大学学报(自然科学版) , 2022 , 50 ( 3 ): 87 - 93 .

DONG H M , AN H P , ZHANG C . Finite element contact modeling method of hermitage teeth based on grid method [J ] . Journal of Huazhong University of Science and Technology (Natural Science Edition) , 2022 , 50 ( 3 ): 87 - 93 . (in Chinese)

熊光明 , 于全富 , 胡秀中 , 等 . 考虑平台特性的多层建筑物内履带式无人平台运动规划 [J ] . 兵工学报 , 2023 , 44 ( 3 ): 841 - 850 . DOI: 10.12382/bgxb.2021.0800 http://doi.org/10.12382/bgxb.2021.0800 针对在多层建筑物内无人平台的自主导航问题，提出一种考虑平台特性的运动规划框架。根据履带式平台的特点，采用零半径转向运动基元方案，并引入维诺路径，提高了全局规划在狭窄环境中的灵活性与安全性。经过分段三次Hermite插值得到平滑的全局路径。基于履带式平台运动模型，在轨迹预测的基础上，利用波阵值来提高局部规划算法在障碍物信息失准情况下的鲁棒性，并结合有限状态机决策模型，实现多楼层间的自主导航任务。对算法进行了仿真与实车实验验证。研究结果表明，新算法能够更好地适应室内环境空间狭窄的特点，同时也证明了在实际环境中的可行性。

XIONG G M , YU Q F , HU X Z , et al . A motion planner for unmanned tracked vehicles in multi-storey buildings considering the characteristics of vehicles [J ] . Acta Armamentarii , 2023 , 44 ( 3 ): 841 - 850 . (in Chinese) DOI: 10.12382/bgxb.2021.0800 http://doi.org/10.12382/bgxb.2021.0800 To solve the navigation problem of the unmanned vehicles in multi-storey buildings, a motion planning framework considering the characteristics of vehicles is proposed. Based on the characteristics of tracked vehicles, the primitive scheme of zero-radius steering is adopted and the Voronoi Path is introduced, which improves the flexibility and safety of the global planner in a narrow environment. Then, the smooth global path is obtained through piecewise cubic Hermite interpolation. Based on model prediction with respecting to the kinematic model of tracked vehicles, the Wavefront Value is introduced to improve the robustness of the local planning algorithm in the case of inaccurate obstacle positioning, and combined with the Finite State Machine to implement the autonomous navigation task between multiple floors. Finally, the simulation and real vehicle experiment are performed. The results show that the proposed algorithm can better adapt to the characteristics of narrow indoor space and also prove its feasibility in the actual environment.

王磊 . 海洋环境下水下机器人快速路径规划研究 [D ] . 哈尔滨 : 哈尔滨工程大学 , 2007 .

WANG L . Research on fast path planning for AUV in ocean environment [D ] . Harbin : Harbin Engineering University , 2007 . (in Chinese)

张舒然 . 基于群智算法的无人机航迹规划研究 [D ] . 成都 : 电子科技大学 , 2020 .

ZHANG S R . Research on UAV track planning based on swarm intelligence algorithm [D ] . Chengdu : University of Electronic Science and Technology of China , 2020 . (in Chinese)

LIU G Y , SHU C , LIANG Z W , et al . A modified sparrow search algorithm with application in 3d route planning for UAV [J ] . Sensors , 2021 , 21 ( 4 ): 1224 . DOI: 10.3390/s21041224 http://doi.org/10.3390/s21041224 https://www.mdpi.com/1424-8220/21/4/1224 https://www.mdpi.com/1424-8220/21/4/1224 The unmanned aerial vehicle (UAV) route planning problem mainly centralizes on the process of calculating the best route between the departure point and target point as well as avoiding obstructions on route to avoid collisions within a given flight area. A highly efficient route planning approach is required for this complex high dimensional optimization problem. However, many algorithms are infeasible or have low efficiency, particularly in the complex three-dimensional (3d) flight environment. In this paper, a modified sparrow search algorithm named CASSA has been presented to deal with this problem. Firstly, the 3d task space model and the UAV route planning cost functions are established, and the problem of route planning is transformed into a multi-dimensional function optimization problem. Secondly, the chaotic strategy is introduced to enhance the diversity of the population of the algorithm, and an adaptive inertia weight is used to balance the convergence rate and exploration capabilities of the algorithm. Finally, the Cauchy–Gaussian mutation strategy is adopted to enhance the capability of the algorithm to get rid of stagnation. The results of simulation demonstrate that the routes generated by CASSA are preferable to the sparrow search algorithm (SSA), particle swarm optimization (PSO), artificial bee colony (ABC), and whale optimization algorithm (WOA) under the identical environment, which means that CASSA is more efficient for solving UAV route planning problem when taking all kinds of constraints into consideration.

张昀普 , 单甘霖 . 道路约束下多传感器协同地面目标跟踪的管理方法 [J ] . 兵工学报 , 2022 , 43 ( 3 ): 542 - 555 . DOI: 10.12382/bgxb.2021.0122 http://doi.org/10.12382/bgxb.2021.0122 为实现道路约束下地面目标的有效跟踪、控制传感器系统的辐射损失，提出一种多传感器协同管理方法。将传感器管理过程描述为部分可观马尔可夫决策过程，建立道路约束下目标跟踪模型和传感器截获损失模型，给出跟踪精度和截获损失的具体计算方法，并提出一种多普勒盲区下的目标预测状态修正方法；针对高维数下管理方案求取困难的问题，设计了一种莱维飞行- 樽海鞘群算法以快速获得高质量的解。仿真实验结果表明：相比于经典寻优算法，所提算法具有更好的全局搜索能力，能够在缩短寻优时间的同时找到高质量的解；所提管理方法能够有效解决地面目标跟踪问题，既保证了跟踪任务的完成质量，又提高了传感器系统的生存能力。

ZHANG Y P , SHAN G L . Multi-sensor cooperative management for ground target tracking under road constraints [J ] . Acta Armamentarii , 2022 , 43 ( 3 ): 542 - 555 . (in Chinese) DOI: 10.12382/bgxb.2021.0122 http://doi.org/10.12382/bgxb.2021.0122 A multi-sensor cooperative management method is proposed to effectively track the ground target under road constraints and control the radiation loss of the sensor system. The sensor management process is described as a partially observable Markov decision process. A road-constrainted target tracking model and a sensor interception loss model are established, the calculation methods for tracking accuracy and interception loss are presented, and a correction method for target prediction state in Doppler blind zone is proposed. In order to solve the problem that a management scheme is difficultly got when the system state dimension is high, a Levy flight-salp swarm algorithm is designed to obtain a high-quality solution quickly. The simulated results show that the proposed algorithm has better global search capability, and can find high-quality solutions while shortening the optimization time compared with the classic optimization algorithms. The proposed management method can effectively solve the problem of ground target tracking, which not only guarantees the completion quality of the tracking task, but also improves the survivability of the sensor system.

宋志强 , 夏庆锋 , 陈少博 , 等 . 基于改进球面向量粒子群优化的UAV航迹规划 [J ] . 电光与控制 , 2023 , 30 ( 4 ): 56 - 60 .

SONG Z Q , XIA Q F , CHEN S B , et al . UAV track planning based on improved spherical vector particle swarm optimization [J ] . Electro-optics & Control , 2023 , 30 ( 4 ): 56 - 60 . (in Chinese)

蔺文轩 , 谢文俊 , 张鹏 , 等 . 基于分组优化改进粒子群算法的无人机三维路径规划 [J ] . 火力与指挥控制 , 2023 , 48 ( 1 ): 20 - 25 ,32.

LIN W X , XIE W J , ZHANG P , et al . UAV three-dimensional path planning based on group optimization and improved particle swarm optimization [J ] . Fire Control & Command Control , 2023 , 48 ( 1 ): 20 - 25 ,32. (in Chinese)

苟进展 , 吴宇 , 邓嘉宁 . 基于群智能-一致性理论的无人机编队全过程飞行航迹规划方法 [J ] . 控制与决策 , 2023 , 38 ( 5 ) : 1464 - 1472 .

GOU J Z , WU Y , DENG J N . Trajectory planning method for UAV formation flight based on swarm intelligence-consistency theory [J ] . Control and Decision , 2023 , 38 ( 5 ): 1464 - 1472 . (in Chinese)

刘晓琴 . 基于GRU的四旋翼无人机飞行姿态估计 [D ] . 桂林 : 桂林电子科技大学 , 2021 .

LIU X Q . Flight attitude estimation of quadrotor UAV based on GRU [D ] . Guilin : Guilin University of Electronic Technology , 2021 . (in Chinese)