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吉林化工学院学报, 2022, 39(7): 34-41     https://doi.org/10.16039/j.cnki.cn22-1249.2022.07.007
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复杂环境下移动机器人路径规划与跟随
王影,杨家鑫**,刘麒*,徐姣姣***
吉林化工学院 信息与控制工程学院,吉林 吉林132022
Path Planning and Following of Mobile Robots in Complex Environments
WANG Ying,  YANG Jiaxin**,  LIU Qi*,  XU Jiaojiao***
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摘要 

提出了一种基于改进A*算法和PID控制算法的新型移动机器人路径规划与路径跟随控制方法,该方法适用于复杂的迷宫环境。在所提出的方法中,解决了A*算法转折点过多的问题,并且通过拓展障碍物和四阶三次均匀B样条优化的方法使生成的预期路径安全且平滑;之后基于前视点的两轮差速机器人运动学模型设计了PID控制器。在专门设计的框架中测试了所提出方法的性能。作为验证,分别从路径规划与路径跟随两个方面做了详尽的实验,结果表明,规划路径转折点少且平滑,设计的PID控制器能够控制移动机器人实现较好的路径跟随效果。最后,在复杂的迷宫环境中验证了本文提出的方法,结果表明,所提出的方法能够使机器人无碰撞穿越迷宫。

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王影
杨家鑫
刘麒
徐姣姣
关键词:  复杂环境  路径规划  路径跟随  A*算法  PID控制     
Abstract: 

This paper proposed a new path planning and path following control method for mobile robots based on improved A* algorithm and PID control algorithm, which is suitable for complex maze environments. In the proposed method, the problem of too many turning points of the A* algorithm is solved, and the generated expected path is safe and smooth by extending the obstacles and the fourth-order cubic uniform B-spline optimization method. Afterwards, a PID controller is designed based on the kinematic model of the two-wheel differential robot based on the forward viewpoint. The performance of the proposed method is tested in a specially designed framework. As a verification, detailed experiments are carried out from the two aspects of path planning and path following. The results show that the planning path has few turning points and the path is smooth, and the designed PID controller can control the mobile robot to achieve better path following effect. Finally, the proposed method is validated in a complex maze environment, and the results show that the proposed method enables the robot to traverse the maze without collision.

Key words:  complex environment    path planning    path following    A* algorithm    PID control
               出版日期:  2022-07-25      发布日期:  2022-07-25      整期出版日期:  2022-07-25
ZTFLH:  TP24  
引用本文:    
王影, 杨家鑫, 刘麒, 徐姣姣. 复杂环境下移动机器人路径规划与跟随 [J]. 吉林化工学院学报, 2022, 39(7): 34-41.
WANG Ying, YANG Jiaxin, LIU Qi, XU Jiaojiao. Path Planning and Following of Mobile Robots in Complex Environments . Journal of Jilin Institute of Chemical Technology, 2022, 39(7): 34-41.
链接本文:  
http://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2022.07.007  或          http://xuebao.jlict.edu.cn/CN/Y2022/V39/I7/34
[1] 高卫斌, 柳晓龙. 基于A*算法的2种任务-处理器分配改进算法 [J]. 吉林化工学院学报, 2021, 38(1): 52-57.
[2] 孟亚男, 冯兼. 差分进化算法在数字PID参数整定中的应用 [J]. 吉林化工学院学报, 2020, 37(5): 38-41.
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