陈慧岩 , 张玉 . 军用地面无人机动平台技术发展综述 [J ] . 兵工学报 , 2014 , 35 ( 10 ): 1696 - 1706 . DOI: 10.3969/j.issn.1000-1093.2014.10.026 http://doi.org/10.3969/j.issn.1000-1093.2014.10.026 地面无人机动平台对发展高机动地面无人战斗系统具有重要的战略意义，是当前各国国防科技领域的研究热点。文中综述了军用地面无人机动平台的发展历程与最新进展，分别阐述和分析了其基本组成和发展特点，然后从环境感知、运动规划、跟踪控制等方面总结了军用地面无人机动平台发展中的关键技术，并对军用无人机动平台的研究方向和研究重点进行了展望。

CHEN H Y , ZHANG Y . An overview of research on military unmanned ground vehicles [J ] . Acta Armamentarii , 2014 , 35 ( 10 ): 1696 - 1706 . (in Chinese)

李睿 , 项昌乐 , 王超 , 等 . 自动驾驶履带车辆鲁棒自适应轨迹跟踪控制方法 [J ] . 兵工学报 , 2021 , 42 ( 6 ): 1128 - 1137 . DOI: 10.3969/j.issn.1000-1093.2021.06.002 http://doi.org/10.3969/j.issn.1000-1093.2021.06.002 针对野外环境中自动驾驶履带车辆轨迹跟踪控制问题，考虑建模误差、参数不确定性及外界随机强干扰，以强鲁棒性及精确跟踪为目标，提出一种基于误差符号鲁棒积分的自动驾驶履带车辆鲁棒自适应轨迹跟踪控制方法。基于拉格朗日动力学方程建立自动驾驶履带车辆的运动学与动力学耦合模型；采用自适应控制方法实现对模型的精确前馈补偿，抵消模型非线性的影响；通过误差符号鲁棒积分有效抑制外界干扰及不确定性的影响；利用Lyapunov稳定性理论证明了闭环系统的全局渐进稳定性与收敛性。对仿真结果进行了实车实验一致性验证。仿真和实验结果证明：该方法在存在建模误差、参数不确定性、外界干扰条件下，在实现自动驾驶履带车辆高精度轨迹跟踪控制的同时，具有较强的自适应和鲁棒性。

LI R , XIANG C L , WANG C , et al. Robust adaptive trajectory tracking control method for autonomous tracked vehicle [J ] . Acta Armamentarii , 2021 , 42 ( 6 ): 1128 - 1137 . (in Chinese)

PULGARIN E J L , IRMAK T , PAUL J V , et al. Comparing model-based and data-driven controllers for an autonomous vehicle task [C ] //Proceedings of Annual Conference Towards Autonomous Robotic Systems . Cham, Germany : Springer , 2018 : 170 - 182 .

WANG H Y , LIU B , PING X Y , et al. Path tracking control for autonomous vehicles based on an improved MPC [J ] . IEEE Access , 2019 , 7 : 161064 - 161073 . DOI: 10.1109/ACCESS.2019.2944894 http://doi.org/10.1109/ACCESS.2019.2944894 In this paper, an improved Model Predictive Control (MPC) controller based on fuzzy adaptive weight control is proposed to solve the problem of autonomous vehicle in the process of path tracking. The controller not only ensures the tracking accuracy, but also considers the vehicle dynamic stability in the process of tracking, i.e., the vehicle dynamics model is used as the controller model. Moreover, the problem of driving comfort caused by the application of classical MPC controller when the vehicle is deviated from the target path is solved. This controller is mainly realized by adaptively improving the weight of the cost function in the classical MPC through the fuzzy adaptive control algorithm. A comparative study which compares the proposed controller with the pure-pursuit controller and the classical MPC controller is made: through the CarSim-Matlab/Simulink co-simulations, the results show that this controller presents better tracking performance than the latter ones considering both tracking accuracy and steering smoothness.

杨福威 , 孟红 , 朱强 . 基于模型预测控制的履带式无人平台轨迹跟踪控制算法研究 [J ] . 舰船电子工程 , 2018 , 38 ( 3 ): 44 - 50 .

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胡家铭 , 胡宇辉 , 陈慧岩 , 等 . 基于模型预测控制的无人驾驶履带车辆轨迹跟踪方法研究 [J ] . 兵工学报 , 2019 , 40 ( 3 ): 456 - 463 . DOI: 10.3969/j.issn.1000-1093.2019.03.002 http://doi.org/10.3969/j.issn.1000-1093.2019.03.002 无人驾驶履带车辆的轨迹跟踪面临着系统不确定性和外界干扰等难以克服的不利因素。针对这一问题，通过研究履带车辆的滑动转向特性，建立了基于瞬时转向中心的履带车辆运动学模型。同时，针对参考路径是离散路点序列的特点，提出了一种基于3次Bezier曲线的参考路径自适应拟合方法，在实现路径平滑基础上提供道路的曲率信息。考虑到模型不确定性和外界干扰对轨迹跟踪精度的影响，设计了基于模型预测控制的轨迹跟踪控制器，并引入反馈校正，系统地处理无人驾驶履带车辆建模误差、环境约束以及执行机构约束。实车试验结果表明，该方法可以有效地抑制系统不确性和外界干扰的影响，实现无人驾驶履带车辆高精度的轨迹跟踪控制。

HU J M , HU Y H , CHEN H Y , et al. Research on trajectory tracking method of unmanned tracked vehicle based on model predictive control [J ] . Acta Armamentarii , 2019 , 40 ( 3 ): 456 - 463 . (in Chinese)

熊光明 , 鲁浩 , 郭孔辉 , 等 . 基于滑动参数实时估计的履带车辆运行轨迹预测方法研究 [J ] . 兵工学报 , 2017 , 38 ( 3 ): 600 - 607 . DOI: 10.3969/j.issn.1000-1093.2017.03.025 http://doi.org/10.3969/j.issn.1000-1093.2017.03.025 要实现履带车辆的无人驾驶，在轨迹规划阶段需要准确预测其未来一段时间内的运动轨迹，然而履带与地面之间的滑动使车辆运动轨迹的准确预测变得非常困难。通过研究转向过程中履带接地段的运动，建立基于瞬时转向中心的履带车辆运动学模型。针对车辆的相对位姿是滑动参数的泛函，雅可比矩阵难以求解的问题，通过对泛函微分方程线性化，推导了雅可比矩阵的解析解。根据车辆相对位置计算值和测量值的差值，运用Levenberg-Marquardt算法迭代求解滑动参数，并结合给定控制序列预测未来一段时间内车辆的运动轨迹。该方法不需要提前知道土壤参数，并且能够实时估计滑动参数，以适应路面变化。实车试验结果表明，与传统轨迹预测方法相比，利用该方法预测车辆轨迹时，车辆位置偏差减少30%以上。

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赵梓烨 , 刘海鸥 , 陈慧岩 . 分布式电驱动无人高速履带车辆越野环境轨迹预测方法研究 [J ] . 兵工学报 , 2019 , 40 ( 4 ): 680 - 688 . DOI: 10.3969/j.issn.1000-1093.2019.04.002 http://doi.org/10.3969/j.issn.1000-1093.2019.04.002 越野环境下，无人车辆轨迹预测是车辆轨迹跟踪和精确导航的核心模块，预测误差将直接影响无人车辆行驶任务完成的准确程度。为实现速差转向式履带车辆在复杂越野环境下无人行驶轨迹准确预测的目的，搭建了分布式电驱动无人履带车辆系统，实现了车辆动态过程中的无人系统数据和车辆底层状态数据的同步采集。建立了速差转向车辆运动学模型，分析了履带车辆滑动转向特性。分别采用扩展卡尔曼滤波(EKF)方法和Levenberg-Marquardt方法对转向过程中的滑动参数进行估计，并完成了车辆轨迹预测。基于真实越野环境下的实车数据进行了验证。试验结果表明：相比于履带车辆理想预测模型，所采用的两种轨迹预测方法都大幅降低了车辆轨迹预测误差；对误差均值而言，EKF方法预测轨迹优于Levenberg-Marquardt方法；对误差标准差而言，后者优于前者，且随着转向程度的增加而增大。

ZHAO Z Y , LIU H O , CHEN H Y . Research on off-road environment trajectory prediction method of distributed electric driven unmanned high-speed tracked vehicle [J ] . Acta Armamentarii , 2019 , 40 ( 4 ): 680 - 688 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2019.04.002 http://doi.org/10.3969/j.issn.1000-1093.2019.04.002 The unmanned vehicle trajectory prediction module is a core module of vehicle trajectory tracking and precise navigation in the off-road conditions. The prediction error has direct effect on the accuracy of the completion of unmanned vehicle driving tasks. In order to realize the accurate prediction of trajectory of skid-steered unmanned tracked vehicle in the complex off-road conditions, a distributed electric drive unmanned tracked vehicle system was built, which realizes the synchronous acquisition of unmanned system data and vehicle state data in the vehicle dynamic process. A kinematic model of skided-steered tracked vehicle is established, and the sliding steering characteristics of tracked vehicle are analyzed. The extended Kalman filter (EKF) method and the Levenberg-Marquardt(L-M) method are used to estimate the sliding parameters in the steering process, and the vehicle trajectory prediction is completed. The verification analysis is based on real vehicle data in real off-road conditions. The statistical analysis method is used to compare the prediction errors of two prediction methods. The test results show that, compared with the ideal prediction model of tracked vehicles, the two trajectory prediction methods greatly reduce the prediction error of vehicle trajectory. For the mean of error, EKF method is better than L-M method in the trajectory prediction; for the standard deviation, the latter is better than the former, and the standard deviation increases with the increase in the degree of steering. Key

QIN Z B , CHEN L , FAN J J , et al. An improved real-time slip model identification method for autonomous tracked vehicles using forward trajectory prediction compensation [J ] . IEEE Transactions on Instrumentation and Measurement , 2021 , 70 : 1 - 12 .

芮强 , 王红岩 , 王钦龙 , 等 . 基于剪应力模型的履带车辆转向力矩分析与试验 [J ] . 兵工学报 , 2015 , 36 ( 6 ): 968 - 977 . DOI: 10.3969/j.issn.1000-1093.2015.06.002 http://doi.org/10.3969/j.issn.1000-1093.2015.06.002 为了研究在打滑条件下的履带车辆转向性能，提高履带车辆转向模型的模拟精度，建立了考虑履带滑转、滑移及转向离心力影响的高速履带车辆稳态转向模型。根据剪切应力-剪切位移关系模型推导了两侧履带牵引力、制动力及转向阻力矩的计算公式。在此基础上，根据力平衡关系构建了履带车辆转向运动学方程，并采用迭代计算方法进行求解。以某型装备综合传动装置的高速履带车辆为对象，通过试验测试结果与计算结果的对比分析，对履带车辆转向模型的准确性进行了验证。基于履带车辆稳态转向模型，研究了履带车辆转向运动学及动力学特性随转向半径及车速的变化规律，结果表明：当履带车辆转向速度越高，转向半径越小时，离心力对转向性能的影响越显著。

RUI Q , WANG H Y , WANG Q L , et al. Analysis and test of steering torque of Tracked Vehicle Based on shear stress model [J ] . Acta Armamentarii , 2015 , 36 ( 6 ): 968 - 977 . (in Chinese)

安杰 , 周志立 , 曹付义 . 履带滑移和转向中心线偏移对车辆稳态转向特性的影响 [J ] . 河南科技大学学报:自然科学版 , 2006 , 27 ( 5 ): 18 - 24 .

AN J , ZHOU Z L , CAO F Y . Influence of track slip and steering centerline offset on vehicle steady-state steering characteristics [J ] . Journal of Henan University of science and technology: Natural Science Edition , 2006 , 27 ( 5 ): 18 - 24 . (in Chinese)