Research on Multi-robot Formation Control Based on Speed Compensation Algorithm
[1]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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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
43
Number of periods:
2022 02
Page number:
1-6
Column:
Public date:
2022-02-27
- Title:
- Research on Multi-robot Formation Control Based on Speed Compensation Algorithm
- Keywords:
- leader-follower algorithm; speed compensation algorithm; tracking control; formation obstacle avoidance control
- CLC:
- TP242.2
- 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.
- References:
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2022-02-25