SONKER R , DUTTA A . Adding terrain height to improve model learning for path tracking on uneven terrain by a four-wheel robot [J ] . IEEE Robotics and Automation Letters , 2020 , 6 ( 1 ): 239 - 246 . DOI: 10.1109/LSP.2016. http://doi.org/10.1109/LSP.2016. https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7083369 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7083369

TAGHAVIFAR H , RAKHEIA S . A novel terramechanics-based path-tracking control of terrain-based wheeled robot vehicle with matched-mismatched uncertainties [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 1 ): 67 - 77 . DOI: 10.1109/TVT.25 http://doi.org/10.1109/TVT.25 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25

GE C , QIAN S Q . An adaptive MPC trajectory tracking algorithm for autonomous vehicles [C ] // Proceedings of the 2021 17th International Conference on Computational Intelligence and Security.Chengdu,China:IEEE , 2021 : 197 - 201 .

SUN Q P , WANG Z H , LI M , et al . Path tracking control of wheeled mobile robot based on improved pure pursuit algorithm [C ] // Proceedings of the 2019 Chinese Automation Congress. Hangzhou, China:IEEE , 2019 : 4239 - 4244 .

ERNÓ H , CSABA H , KÓRÖS P . Novel Pure-Pursuit trajectory following approaches and their practical applications [C ] // Proceedings of the 2019 10th IEEE International Conference on Cognitive Infocommunic-Ations. Naples , Italy : IEEE , 2019 : 597 - 602 .

HUA Q , PENG B S , MOU X L , et al . Model prediction control path tracking algorithm based on adaptive stanley [C ] // Proceedings of the 2022 IEEE 96th Vehicular Technology Conference.London , UK : IEEE , 2022 : 1 - 5 .

ZUO Z Q , YANG X , LI Z , et al . MPC-based cooperative control strategy of path planning and trajectory tracking for intelligent vehicles [J ] . IEEE Transactions on Intelligent Vehicles , 2020 , 6 ( 3 ): 513 - 522 . DOI: 10.1109/TIV.2020.3045837 http://doi.org/10.1109/TIV.2020.3045837 https://ieeexplore.ieee.org/document/9298806/ https://ieeexplore.ieee.org/document/9298806/

ZHAI L , WANG C P , HOU Y H , et al . MPC-based integrated control of trajectory tracking and handling stability for intelligent driving vehicle driven by four hub motor [J ] . IEEE Transactions on Vehicular Technology , 2022 , 71 ( 3 ): 2668 - 2680 . DOI: 10.1109/TVT.2022.3140240 http://doi.org/10.1109/TVT.2022.3140240 https://ieeexplore.ieee.org/document/9669013/ https://ieeexplore.ieee.org/document/9669013/

LI Z J , DENG J , LU R Q , et al . Trajectory-tracking control of mobile robot systems incorporating neural-dynamic optimized model predictive approach [J ] . IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2016 , 46 ( 6 ): 740 - 749 . DOI: 10.1109/TSMC.6221021 http://doi.org/10.1109/TSMC.6221021 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221021 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221021

CHU D F , LI H R , ZHAO C Y , et al . Trajectory tracking of autonomous vehicle based on model predictive control with PID feedback [J ] . IEEE Transactions on Intelligent Transportation Systems , 2023 , 24 ( 2 ): 2239 - 2250 .

YANG H J , FAN X Z , SHI P , et al . Nonlinear control for tracking and obstacle avoidance of a wheeled mobile robot with nonholonomic constraint [J ] . IEEE Transactions on Control Systems Technology , 2016 , 24 ( 2 ): 741 - 746 .

ZHANG X L , ZHANG W X , ZHAO Y Q , et al . Personalized motion planning and tracking control for autonomous vehicles obstacle avoidance [J ] . IEEE Transactions on Vehicular Technology , 2022 , 71 ( 5 ): 4733 - 4747 . DOI: 10.1109/TVT.2022.3152542 http://doi.org/10.1109/TVT.2022.3152542 https://ieeexplore.ieee.org/document/9716824/ https://ieeexplore.ieee.org/document/9716824/

GUO B H , GUO N , CEN Z S . Obstacle avoidance with dynamic avoidance risk region for mobile robots in dynamic environments [J ] . IEEE Robotics and Automation Letters , 2022 , 7 ( 3 ): 5850 - 5857 . DOI: 10.1109/LRA.2022.3161710 http://doi.org/10.1109/LRA.2022.3161710 https://ieeexplore.ieee.org/document/9740452/ https://ieeexplore.ieee.org/document/9740452/

GUO H Y , SHEN C , ZHANG H , et al . Simultaneous trajectory planning and tracking using an MPC method for cyber-physical systems: a case study of obstacle avoidance for an intelligent vehicle [J ] . IEEE Transactions on Industrial Informatics , 2018 , 74 ( 9 ): 4273 - 4283 .

LU Q , ZHANG D , YE W J , et al . Targeting posture control with dynamic obstacle avoidance of constrained uncertain wheeled mobile robots including unknown skidding and slipping [J ] . IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2021 , 51 ( 11 ): 6650 - 6659 . DOI: 10.1109/TSMC.2019.2962732 http://doi.org/10.1109/TSMC.2019.2962732 https://ieeexplore.ieee.org/document/8962121/ https://ieeexplore.ieee.org/document/8962121/

XIANG L D , LI X M , LIU H , et al . Parameter fuzzy self-adaptive dynamic window approach for local path planning of wheeled robot [J ] . IEEE Open Journal of Intelligent Transportation Systems , 2022 , 3 : 1 - 6 . DOI: 10.1109/OJITS.2021.3137931 http://doi.org/10.1109/OJITS.2021.3137931 https://ieeexplore.ieee.org/document/9662076/ https://ieeexplore.ieee.org/document/9662076/

LYNCH K M , PARK F C . Modern robotics: mechanics, planning, and control [M ] . Beijing : China Machine Press , 2019 : 328 - 350 .

严浙平 , 杨皓宇 , 张伟 , 等 . 基于模型预测—中枢模式发生器的六足机器人轨迹跟踪控制 [J ] . 机器人 , 2023 , 45 ( 1 ): 58 - 69 .

YAN Z P , YANG H Y , ZHANG W , et al . Trajectory tracking control of hexapod robot based on model prediction and center pattern generator [J ] . Robot , 2023 , 45 ( 1 ): 58 - 69 . (in Chinese)

RASHIDI B , ESMAEILPOOR M , HOMAEINEZHAD M R , et al . Error-based self-regulating PID angle control of variable structure redundant brushed DC motors [C ] // Proceedings of the 2014 Second RSI/ISM International Conference on Robotics and Mechatronics. Tehran, Iran:IEEE , 2014 : 274 - 279 .

张超省 , 王健 , 张林 , 等 . 面向复杂障碍场的多智能体系统集群避障模型 [J ] . 兵工学报 , 2021 , 42 ( 1 ): 141 - 150 .

ZHANG C S , WANG J , ZHANG L , et al . A multi-agent system flocking model with obstacle avoidance in complex obstacle field [J ] . Acta Armamentarii , 2021 , 42 ( 1 ): 141 - 150 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2021.01.016 http://doi.org/10.3969/j.issn.1000-1093.2021.01.016 A multi-agent system flocking model with obstacle avoidance in complex obstacle field is established for the obstacle avoidance of robot flock in the ground battlefield. In this model, the complex obstacle is geometrically described with polygon shape, which reduces the probability of channel narrowing or blocking caused by the least circumscribed circle(ball). Based on the artificial potential method, a mathematical model and the solving flow are presented for the interactions between agents, agent and surrounding obstacles, agent and its target. When solving the model, the rejective edge and rejective area of polygon obstacle are determined from the relationship among the outer center of agent and the geometric properties of polygon obstacle, including inner center, outer center and edge, and the capturing edge of polygon obstacle and the temporary target of agent are determined from the relationship among the outer center of agent, the edge of polygon obstacle and the target, thus overcoming the defect that the agent is usually captured by the edge of polygon obstacle. The simulated results show that the proposed model can be used to control the flocking with obstacle avoidance of multi-agent system whether for static target or dynamic target.

邓海鹏 , 麻斌 , 赵海光 , 等 . 自主驾驶车辆紧急避障的路径规划与轨迹跟踪控制 [J ] . 兵工学报 , 2020 , 41 ( 3 ): 585 - 594 . DOI: 10.3969/j.issn.1000-1093.2020.03.020 http://doi.org/10.3969/j.issn.1000-1093.2020.03.020 为减少道路突发事故，提高车辆通行效率，需要研究车辆的紧急避障以实现自主驾驶。基于车辆点质量模型，设计了非线性模型预测控制（MPC）路径规划器；基于车辆动力学模型，设计了线性时变MPC轨迹跟踪器。在路径规划层引入避障功能函数，通过车辆与障碍物的距离调节函数值大小，综合避障函数权重和路径偏差权重，规划出一条既能避开障碍物又使路径偏差最小的临时轨迹。在轨迹跟踪层，利用该临时轨迹和航向角偏差作为车辆主动转向控制参考量，将线性时变MPC优化问题转化为二次规划问题，计算满足车辆动力学约束的前轮转向角最优解。结果表明：所设计的双层MPC紧急避障控制策略对低速(60 km/h)、中速(80 km/h)、高速(100 km/h)行驶车辆有很强的适应性，高速行驶时最大质心侧偏角不超过1.0°，最大航向角偏差不超过2.5°，车辆横向稳定性良好，随着车速增大，车辆避障响应时刻提前；在多车连续避障场景中，自主驾驶车辆的质心侧偏角和航向角偏差均能控制在较小范围内，在多目标连续避障的路径规划和轨迹跟踪问题上同样具有很好的控制效果。

DENG H P , MA B , ZHAO H G , et al . Path planning and tracking control of autonomous vehicle for obstacle avoidance [J ] . Acta Armamentarii , 2020 , 41 ( 3 ): 585 - 594 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2020.03.020 http://doi.org/10.3969/j.issn.1000-1093.2020.03.020 Emergency obstacle avoidance is one of the key points for autonomous driving system. A path planning controller based on non-linear model predictive control and a path tracking controller based on linear time-varying model predictive control are designed.In path planning controller，an obstacle-avoiding function is used to adjust the distance between the intelligent vehicle and obstacles by calculating the value of obstacle-avoiding function.A new route is supposed to be planned，which can not only keep away from obstacles but also decrease the deviations from the global course，by considering the different weights of obstacle-avoiding function and the planning error. In path tracking controller，the solution of linear time-varying model predictive control is converted into a positive-definite quadratic program.And then the desired steering angles of front wheel are calculated by using the reference trajectory and orientation angle of vehicle center. The results show that the obstacle-avoiding controller has strong robustness and the path tracking controller has better performance in controlling accuracy and vehicle dynamics stability when a vehicle travels at 60 km/h，80 km/h，or 100 km/h. The maximal side-slip angle is no more than 1°，and the maximal deviation of yaw angle is less than 2.5°.Obstacle avoiding action occurs in advance with the increase in velocity of autonomous vehicle. In addition，the dual-MPC controller is adaptive to the circumstance of multi-obstacles avoidance as well，which can be easily demonstrated by the small deviation of yaw angles and small side-slip angles.Key

杜广泽 , 张旭东 , 邹渊 , 等 . 非结构道路场景下轮式无人车辆避障算法 [J ] . 兵工学报 , 2020 , 41 ( 10 ): 2096 - 2105 . DOI: 10.3969/j.issn.1000-1093.2020.10.020 http://doi.org/10.3969/j.issn.1000-1093.2020.10.020 针对非结构化道路下轮式无人车辆的避障问题，提出一种基于模型预测控制的避障算法。在没有离线地图和参考轨迹的非结构化场景下，通过优化方法直接获得车辆运动的轨迹、前轮转角与参考纵向加速度，同时满足车辆运动约束与避障功能。利用车辆感知信息，根据非结构化道路场景将避障问题划分为分段最优控制问题；明确最优控制问题各段的车辆约束与评价指标，并将约束转换为与车辆横纵向控制相关的形式，进而对最优控制问题进行求解。实车测试结果表明，该算法在非结构道路中实现了轨迹规划，规划结果满足车辆约束并使得车辆实现避障。

DU G Z , ZHANG X D , ZOU Y , et al . Obstacle avoidance algorithm for autonomous wheeled vehicle in unstructured environments [J ] . Acta Armamentarii , 2020 , 41 ( 10 ): 2096 - 2105 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2020.10.020 http://doi.org/10.3969/j.issn.1000-1093.2020.10.020 An obstacle avoidance algorithm based on model prediction control is proposed for the obstacle avoidance task of autonomous ground vehicle in unstructured environments. The trajectory of vehicle, steering angle and reference acceleration can be generated by using optimization method without the offline map and the reference trajectory in unstructured environments, and the result satisfies the vehicle motion constraint in passable area. Obstacle avoidance problem is divided into multi-phrases optimal control problem by using the environment perception results according to unstructured road scenarios. The vehicle constraints and cost function for each phrase of the optimal control problem are clarified. The constraints are transformed into the formulation related to vehicle longitudinal and lateral control. Then the optimal control problem is solved by mathematical method. The results of real vehicle tests show that the proposed algorithm can generate trajectory in unstructured environments. It is also shown that the algorithm is capable for obstacle avoidance and keeps vehicle under the limits of constraint.

张家闻 , 房浩霖 , 李家旺 . 基于复杂约束条件的欠驱动AUV三维路径规划 [J ] . 兵工学报 , 2022 , 43 ( 6 ): 1407 - 1414 . DOI: 10.12382/bgxb.2021.0340 http://doi.org/10.12382/bgxb.2021.0340 为解决欠驱动自主水下航行器（AUV）在复杂水域下的三维路径规划和避碰问题，结合欠驱动的运动特性与自身约束条件，提出一种改进的蚁群结合3次B样条曲线拟合的算法，模拟现实海域环境信息进行水下空间环境建模。针对传统蚁群算法规划出的全局路径转角大、曲折多所造成的欠驱动AUV舵轮使用寿命低的问题，采用垂直面安全域设置的方法，设计基于低崎岖度的适应度函数结合路径长度与平缓度的双边评价体系规划出全局路径。采用3次B样条曲线，基于原型值点及目标点速度矢量约束拟合出一条曲率连续、无碰撞的优化路径。仿真结果表明，在保证收敛速度和全局搜索能力的前提下，所规划的路径合理，满足欠驱动AUV运动条件。

ZHANG J W , FANG H L , LI J W . 3D Path planning of underactuated AUV based on complex constraints [J ] . Acta Armamentarii , 2022 , 43 ( 6 ): 1407 - 1414 . (in Chinese) DOI: 10.12382/bgxb.2021.0340 http://doi.org/10.12382/bgxb.2021.0340 An improved ant colony algorithm based on third-order B-spline curve fitting is proposed for the 3-D path planning and collision avoidance of underactuated AUV in complex waters，in which the underactuated motion characteristics and vehicle constraints are considered. An underwater space environment is modeled by simulating the real sea environment complexity. For the short service life issue of the underactuated AUV steering wheel，which is caused by large angle of turn and zigzagging route coming from the global path planned by original ant colony algorithm，a global path is planned by setting a vertical safety zone and redesigning the fitness function and evaluation function based on the factors of short path length and high path smoothness.TAn optimized path is fitted by using B-spline curve. And the continuous and safe path trajectory satisfies the velocity vector constraint of goal point. The simulated results show that the planned path is feasible on the precondition of guaranteeing the high convergence speed and global search capability.