基于改进虚拟弹簧模型的多机器人编队控制

doi:10.16182/j.issn1004731x.joss.22-0197

系统仿真学报 ›› 2023, Vol. 35 ›› Issue (6): 1235-1244.doi: 10.16182/j.issn1004731x.joss.22-0197

基于改进虚拟弹簧模型的多机器人编队控制

陈奕梅(), 石小凡(), 李宝全

天津工业大学控制科学与工程学院，天津 300387

收稿日期:2022-03-10 修回日期:2022-04-27 出版日期:2023-06-29 发布日期:2023-06-20
通讯作者: 石小凡 E-mail:chenplum0301@163.com;sxfholly@163.com
作者简介:陈奕梅(1972-)，女，副教授，博士，研究方向为机器人控制技术。E-mail：chenplum0301@163.com
基金资助:
国家自然科学基金面上项目(61973234)

Multi-robot Formation Control Based on Improved Virtual Spring Model

Yimei Chen(), Xiaofan Shi(), Baoquan Li

College of Electrical Engineering and Automation, Tiangong University, Tianjin 300387, China

Received:2022-03-10 Revised:2022-04-27 Online:2023-06-29 Published:2023-06-20
Contact: Xiaofan Shi E-mail:chenplum0301@163.com;sxfholly@163.com

摘要/Abstract

摘要：

针对多机器人系统在未知环境中难以有效避障和保持队形的问题，在改进虚拟弹簧模型的基础上，提出了一种协同编队避障控制算法。在结合领航者-跟随者方法的基础上引入了虚拟弹簧模型调节，解决了编队中易碰、脱离队形的问题；建立机器人与目标点的牵引力公式，设计可调节阻尼的障碍物虚拟弹簧模型，完成机器人的避障行为；对一些复杂的凹形障碍物，通过引入附加旋转力场的概念，降低了决策的盲目性，解决了编队过程中产生的目标点不可达和局部最优问题。通过仿真与实物实验验证了所提方法的有效性。

关键词: 移动机器人, 编队控制, 避障, 虚拟弹簧, 附加旋转力场

Abstract:

Aiming at multi-robot system being difficult to avoid obstacles and maintain formation in unknown environment, a cooperative formation obstacle avoidance control algorithm based on the improved virtual spring model is proposed. The virtual spring model is introduced on the basis of leader-follower formation approach, which solves the problems of easy touch and out of formation. The attractive elastic force formula between the robot and the target point is established, and the virtual spring model of the obstacle with adjustable damping is designed to complete the obstacle avoidance behavior of robot. Aiming at some complex concave obstacles, the concept of additional rotational force field is introduced to reduce the blindness of decision-making, and solve the problems of unreachable target points and local minima in formation process. The simulation results and physical experiments verify the effectiveness of the proposed algorithm.

Key words: multi-robot, formation control, collision avoidance, virtual spring, additional rotational force field

中图分类号:

TP391.9

陈奕梅, 石小凡, 李宝全. 基于改进虚拟弹簧模型的多机器人编队控制[J]. 系统仿真学报, 2023, 35(6): 1235-1244.

Yimei Chen, Xiaofan Shi, Baoquan Li. Multi-robot Formation Control Based on Improved Virtual Spring Model[J]. Journal of System Simulation, 2023, 35(6): 1235-1244.

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参考文献 16

1	Yang Ziwen, Zhu Shanying, Chen Cailian, et al. Leader-follower Formation Control of Nonholonomic Mobile Robots with Bearing-only Measurements[J]. Journal of the Franklin Institute, 2020, 357(3): 1628-1643.
2	Wang Yuanzhe, Wang Danwei, Yang Shuai, et al. A Practical Leader-follower Tracking Control Scheme for Multiple Nonholonomic Mobile Robots in Unknown Obstacle Environments[J]. IEEE Transactions on Control Systems Technology, 2019, 27(4): 1685-1693.
3	Jiang Chao, Chen Zhuo, Guo Yi. Multi-robot Formation Control: A Comparison between Model-Based and Learning-based Methods[J]. Journal of Control and Decision, 2020, 7(1): 90-108.
4	张玉超, 蒋沅, 代冀阳. 三阶多机器人协同编队动态避障控制[J]. 系统仿真学报, 2022, 34(8): 1762-1774.
	Zhang Yuchao, Jiang Yuan, Dai Jiyang. Dynamic Obstacle Avoidance Control of Three-order Multi-robot Cooperative Formation[J]. Journal of System Simulation, 2022, 34(8): 1762-1774.
5	Khatib O. Real-time Obstacle Avoidance for Manipulators and Mobile Robots[M]. New York: Springer, 1986: 396-404.
6	Alonso-Mora J, Baker S, Rus D. Multi-robot Formation Control and Object Transport in Dynamic Environments via Constrained Optimization[J]. The International Journal of Robotics Research, 2017, 36(9): 1000-1021.
7	Dong Longfei, Chen Yangzhou, Qu Xiaojun. Formation Control Strategy for Nonholonomic Intelligent Vehicles Based on Virtual Structure and Consensus Approach[J]. Procedia Engineering, 2016, 137: 415-424.
8	刘翰培, 王东署, 汪宇轩, 等. 移动机器人路径规划的模糊人工势场法研究[J]. 控制工程, 2022, 29(1): 33-38.
	Liu Hanpei, Wang Dongshu, Wang Yuxuan, et al. Research of Path Planning for Mobile Robots Based on Fuzzy Artificial Potential Field Method[J]. Control Engineering of China, 2022, 29(1): 33-38.
9	Zhang H, Li M, Wu Z. Path Planning Based on Improved Artificial Potential Field Method[C]//33rd Chinese Control and Decision Conference. China: IEEE, 2021: 4922-4925.
10	徐胜, 邢强, 王浩. 解决势场法路径规划中局部极小问题的角度累积法[J]. 控制与决策, 2022, 37(8): 1997-2007.
	Xu Sheng, Xing Qiang, Wang Hao. Angle Accumulation Method for Solving Local Minimum Problem in Path Planning with Potential Field Method[J]. Control and Decision, 2022, 37(8): 1997-2007.
11	Shucker B, Bennett J K. Virtual Spring Mesh Algorithms for Control of Distributed Robotic Macrosensors[R]. Boulder, USA: University of Colorado at Boulder, 2005: 136.
12	高申勇, 许方镇, 郭鸿杰. 基于弹簧模型的移动机器人路径规划研究[J]. 仪器仪表学报, 2016, 37(4): 796-803.
	Gao Shenyong, Xu Fangzhen, Guo Hongjie. Research on Mobile Robots' Path Planning Based on a Spring Model[J]. Chinese Journal of Scientific Instrument, 2016, 37(4): 796-803.
13	Wiech J, Eremeyev V A, Giorgio I. Virtual Spring Damper Method for Nonholonomic Robotic Swarm Self-organization and Leader Following[J]. Continuum Mechanics and Thermodynamics, 2018, 30(5): 1091-1102.
14	Pan Zhenhua, Wang Di, Deng Hongbin, et al. A Virtual Spring Method for the Multi-robot Path Planning and Formation Control[J]. International Journal of Control Automation and Systems, 2019, 17(5): 1272-1282.
15	Liang Xinwu, Wang Hesheng, Liu Yunhui, et al. Leader-following Formation Control of Nonholonomic Mobile Robots with Velocity Observers[J]. IEEE/ASME Transactions on Mechatronics, 2020, 25(4): 1747-1755.
16	Dang A D, La H M, Nguyen T, et al. Formation Control for Autonomous Robots with Collision and Obstacle Avoidance Using a Rotational and Repulsive Force-based Approach[J]. International Journal of Advanced Robotic Systems, 2019, 16(3): 1729881419847897.

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基于改进虚拟弹簧模型的多机器人编队控制

Multi-robot Formation Control Based on Improved Virtual Spring Model

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