[1]张方方,张文丽,王婷婷.基于速度补偿算法的多机器人编队控制研究[J].郑州大学学报(工学版),2022,43(02):1-6.[doi:10.13705/j.issn.1671-6833.2022.02.004]
　ZHANG Fangfang,ZHANG Wenli,WANG Tingting.Research on Multi-robot Formation Control Based on Speed Compensation Algorithm[J].Journal of Zhengzhou University (Engineering Science),2022,43(02):1-6.[doi:10.13705/j.issn.1671-6833.2022.02.004]
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基于速度补偿算法的多机器人编队控制研究()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
43
期数:
2022年02期
页码:
1-6
栏目:
出版日期:
2022-02-27

文章信息/Info

Title:
Research on Multi-robot Formation Control Based on Speed Compensation Algorithm
作者:
张方方; 张文丽; 王婷婷
郑州大学电气工程学院;

Author(s):
ZHANG Fangfang;  ZHANG Wenli;  WANG Tingting
School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
关键词:
Keywords:
leader-follower algorithm;  speed compensation algorithm;  tracking control;  formation obstacle avoidance control
分类号:
TP242.2
DOI:
10.13705/j.issn.1671-6833.2022.02.004
文献标志码:
A
摘要:
为了解决传统领航-跟随法在编队控制中实现较难和算法复杂以及整体编队太依赖领航者的问题，本文在传统领航-跟随算法的基础上，考虑到圆形编队不同于直线编队，传统控制律可能无法完成圆形编队，本文采用“以直代曲”的思想对原控制律进行改进，设计跟随控制器，使得跟随者无论在直线编队中还是在圆形编队中都能够很好地跟随领航者。并提出基于位置信息的速度补偿算法，利用系统内机器人的位置信息设计控制器，减少调用参数的数量，提高编队效率。对于环境中可能存在的障碍物问题，本文将速度补偿算法与传统人工势场法相结合，设计了多机器人编队避障控制方法，保证多机器人系统在行进过程中维持编队运行的同时不仅能够避免机器人之间相互碰撞，也能够自适应避开周围环境中的障碍物。本文所提方法在多机器人仿真和实物平台上进行验证，结果表明多机器人不仅能够高效率地完成编队任务而且在遇到障碍物时能够成功完成避障任务，这也证明了所提方法的有效性和优越性。
Abstract:
In order to solve the problems of complex algorithm of traditional leader-follower method in formation control of multi-robot system and difficulty in completing circular formation of multi-robot system with common formation control law, the formation problem of multi-robot system was transformed into tracking control problem among robots by improving the traditional leader-follower method, and a velocity compensation algorithm based on position information for multi-robot formation was proposed in this study. The formation control model of robot with velocity compensation algorithm is established, and the formation control law was designed based on the pose error between the following robot and the virtual robot, and it is proved theoretically that the proposed control law could complete the multi-robot formation task. Then, on the basis of studying the multi-robot formation problem, the obstacle avoidance problem in the multi-robot formation process is further studied. The classical artificial potential field method was introduced, and the artificial potential field method was combined with the speed compensation algorithm of this study. The combined algorithm could enable the multi-robot system to maintain formation operation, and not only preventing the robots in the system from colliding with each other, but also adaptively avoiding obstacles in the surrounding environment. The results showed that multi-robots could not only complete the formation task efficiently but also successfully complete the obstacle avoidance task when encountering obstacles. Finally, the proposed algorithm was verified by experiments on multi-robot simulation and physical platform. The algorithm could reduce the number of calling parameters, simplified the formation algorithm, and improve the formation efficiency.

参考文献/References:

[1] 魏丁丁.动态环境下多机器人编队路径规划研究[D].邯郸:河北工程大学,2017.

[2] 郭锦荣.多机器人系统编队控制研究[D].北京:华北电力大学,2016.

更新日期/Last Update: 2022-02-25