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牛秦玉 , 李美凡 , 赵勇 . 改进人工势场法的AGV路径规划算法研究 [J ] . 机床与液压 , 2022 , 50 ( 17 ): 19 - 24 . DOI: 10.3969/j.issn.1001-3881.2022.17.004 http://doi.org/10.3969/j.issn.1001-3881.2022.17.004 针对传统人工势场法路径规划中存在的局部极小值和目标不可达问题，提出了一种面向AGV路径规划的改进人工势场法。该算法将道路边界障碍化，对障碍物密集区域的障碍物进行连锁处理，在斥力函数中引入目标点与AGV间的距离因数，在局部极小值点附近合适位置增加虚拟障碍物。仿真结果表明：改进算法可以有效解决局部极小值问题和目标不可达问题，同时使AGV避开障碍物陷阱成功到达目标点。

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李二超 , 王玉华 . 改进人工势场法的移动机器人避障轨迹研究 [J ] . 计算机工程与应用 , 2022 , 58 ( 6 ): 296 - 304 . DOI: 10.3778/j.issn.1002-8331.2108-0122 http://doi.org/10.3778/j.issn.1002-8331.2108-0122 针对传统人工势场法在多障碍物复杂环境的全局路径规划中出现的目标不可达、易陷入陷阱区域以及局部极小点问题，提出一种简化障碍物预测碰撞人工势场法（simplified obstacles and predict collision of artificial potential field method，SOPC-APF），算法引入预测碰撞思想，在机器人未进入陷阱区域或者极小点问题前做出决策；对于多障碍物的斥力与目标点的引力产生的合力使机器人陷入震荡，提出简化障碍物，即简化为影响范围内目标点一侧的受限障碍物；针对目标不可达问题，在碰撞预测基础上，设定虚拟目标点，经改进的斥力函数引导机器人快速生成一条平滑、平稳、无碰撞的路径。通过与传统算法、改进APF算法以及改进蚁群算法的仿真对比实验表明，SOPC-APF有效解决了人工势场法不适用于多障碍物复杂环境的问题，以及传统算法容易陷入陷阱区域和局部极小点问题。

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王威 , 陈慧岩 , 马建昊 , 等 . 基于Frenet坐标系和控制延时补偿的智能车辆路径跟踪 [J ] . 兵工学报 , 2019 , 40 ( 11 ): 2336 - 2351 . DOI: 10.3969/j.issn.1000-1093.2019.11.019 http://doi.org/10.3969/j.issn.1000-1093.2019.11.019 对智能车辆路径跟踪问题中存在的控制延时问题进行研究。前轮转角表述为纯滞后和1阶惯性延时的串联结构模型，通过使用Matlab/Simulink建立转向控制延时模型，并对实车采集的转向控制数据进行分析，完成延时模型的参数辨识；基于V-REP和ROS搭建仿真测试平台，根据延时模型的辨识结果模拟转向响应特性，实现与实车转向特性等效的控制延时效果；基于Frenet坐标系和运动学、动力学模型构建不考虑控制延时和考虑控制延时的模型预测控制(MPC)路径跟踪控制器，使得控制器可以直接扩展到多车编队行驶场景；在V-REP仿真环境中设置以5 m/s、10 m/s、20 m/s车 速采集的变曲率参考路径，先针对无延时系统考察不考虑控制延时的MPC路径跟踪控制器，获得了平均跟踪误差低于0.22 m的控制效果，验证了不考虑控制延时的MPC控制器在处理无延时车辆系统路径跟踪问题的跟踪性能，再针对大延时车辆系统对比测试两种MPC控制器。试验结果表明：考虑控制延时的MPC控制器相比不考虑控制延时的MPC控制器取得了较大的效果提升，特别是在最大跟踪误差和航向误差指标上表现优异，平均跟踪误差降低了83.7%，最大跟踪误差降低了74.4%；对于高延时系统，低速工况下考虑延时的运动学MPC表现更好，而高速工况动力学MPC表现出了更加稳定的跟踪性能，20 m/s延时试验中仅考虑控制延时的动力学MPC控制器安全地跑完了全程。

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