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基于强化学习的激光导航无人车路径跟踪控制

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针对智能仓储无人车运动轨迹控制精度的问题,提出了一种基于强化学习的激光导航无人车路径跟踪控制算法.建立了智能仓储无人车的数学模型,设计了一种激光导航定位算法,提出了一种Actor-Critic强化学习路径跟踪算法,最终实现对无人车路径跟踪的高精度控制.通过对比仿真验证了设计的路径跟踪算法具有更优的控制效果和更高的控制精度,最大路径跟踪误差仅为0.3m,最大x坐标跟踪误差仅为0.1m,最大y坐标跟踪误差仅为0.29 m,大幅提高了对仓储无人车运动轨迹的跟踪精度.
Path tracking control based on reinforcement learning of laser navigation unmanned vehicle
Aiming at the problem of control accuracy of movement trajectory for intelligent storage unmanned vehicle,a path tracking control algorithm based on reinforcement learning of laser navigation unmanned vehicle was proposed.The mathematical model of intelligent storage unmanned vehicle was established,a laser navigation positioning algorithm was designed,and an Actor-Critic reinforcement learning path tracking algorithm was proposed.The high precision control of unmanned vehicle path tracking was realized.The comparative simulation verifies that the as-designed path tracking algorithm has better control effect and higher control accuracy.The maximum path tracking error is only 0.3 m;the maximum x-coordinate tracking error is only 0.1 m;the maximum y-coordinate tracking error is only 0.29 m,greatly improving the tracking accuracy of the motion trajectory of storage unmanned vehicle.

intelligent storageunmanned vehiclelaser navigationpath trackinglocation algorithmreinforcement learningtracking controlhigh accuracy

母军臣、何洪辉

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开封大学 信息工程学院,河南 开封 475000

河南大学 软件学院,河南 郑州 450046

智能仓储 无人车 激光导航 路径跟踪 定位算法 强化学习 跟踪控制 高精度

国家自然科学基金河南省科技攻关计划河南省高等学校重点科研项目开封市科技攻关计划

6170218522210221012523B5200421401011

2024

10.7688/j.issn.1000-1646.2024.02.14

沈阳工业大学学报
沈阳工业大学

沈阳工业大学学报

CSTPCD北大核心
影响因子：0.62
ISSN：1000-1646
年,卷(期)：2024.46(2)
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