嵌套运动饱和下分布式多移动机器人反振荡安全编队控制

郑志; 江涛; 杨玥; 苏晓杰

doi:10.16383/j.aas.c240444

嵌套运动饱和下分布式多移动机器人反振荡安全编队控制

doi: 10.16383/j.aas.c240444 cstr: 32138.14.j.aas.c240444

郑志^1,,
江涛^1,,
杨玥^2,,
苏晓杰^1,

1.
重庆大学自动化学院重庆 400044
2.
西安建筑科技大学信息与控制工程学院西安 710311

基金项目: 国家自然科学基金(62173051, 62106027, 62306228), 陕西省重点研发项目(2024GX-YBXM-132)资助

详细信息

作者简介:
郑志：重庆大学自动化学院博士研究生. 2020年获得哈尔滨工程大学硕士学位. 主要研究方向为多智能体系统协同. E-mail: zhizheng@cqu.edu.cn

江涛：重庆大学自动化学院副教授. 2020年获得北京理工大学博士学位. 主要研究方向为飞行器控制与轨迹规划. 本文通信作者. E-mail: jiangtao_1992@cqu.edu.cn

杨玥：西安建筑科技大学信息与控制工程学院副教授. 2022年获得重庆大学博士学位. 主要研究方向为智能控制与自主无人系统应用. E-mail: yangyue@xauat.edu.cn

苏晓杰：重庆大学自动化学院教授. 2013年获哈尔滨工业大学控制科学与工程博士学位. 主要研究方向为智能控制系统及其在无人系统中的应用. E-mail: suxiaojie@cqu.edu.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2024-06-30
- 录用日期: 2024-10-09
- 网络出版日期: 2024-12-11

Distributed Multi-mobile Robot Anti-oscillation Safety Formation Control with Nested Motion Saturation

ZHENG Zhi^1
,,
JIANG Tao^1
,,
YANG Yue^2
,,
SU Xiao-Jie^1
,

1.
School of Automation, Chongqing University, Chongqing 400044
2.
College of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710311

Funds: Supported by National Natural Science Foundation of China (62173051, 62106027, 62306228), Key Research and Development Program of Shaanxi (2024GX-YBXM-132)

More Information

Author Bio:
ZHENG Zhi　Ph.D. candidate at the School of Automation, Chongqing University. He received his master degree from Harbin Engineering University in 2020. His research interest covers multi-agent coordination

JIANG Tao　Associate professor at the School of Automation, Chongqing University. He received his Ph.D. degree from Beijing Institute of Technology in 2020. His research interest covers aircraft control and trajectory planning. Corresponding author of this paper

YANG Yue　Associate professor at College of Information and Control Engineering, Xi'an University of Architecture and Technology. She received her Ph.D. degree from Chongqing University in 2022. Her research interest covers Intelligent control and application of autonomous unmanned systems

SU Xiao-Jie　Professor at the College of Automation, Chongqing University. He received Ph.D. degree in control theory and control engineering from the Harbin Institute of Technology, Harbin, in 2013. His current research interests include intelligent control systems, advanced control and system analysis, and application of intelligent robot control

摘要

摘要: 运动受速度和加速度嵌套饱和约束, 而反应式躲避安全机制下分布式编队互联的移动机器人更易触发该嵌套饱和, 从而引起编队的剧烈振荡, 所以需要研究该情况下多移动机器人平滑安全协同及其振荡自适应抑制方法. 本文以分布式网络中的移动机器人为研究对象, 首先构建基于视线和速度的低触发势能函数, 实现邻近编队机器人近距排斥作用下的避碰保持; 引入驱动机器人绕过障碍物的安全加速度包络, 并复合近距排斥的弱能量、低触发势能, 避免与非合作障碍物的碰撞. 其次, 嵌入复合自适应辅助动态系统, 平滑躲避过程中触发的嵌套运动饱和和安全加速度约束引起的轨迹振荡; 设计复合非线性反馈框架下的分布式编队控制器, 融合混合的躲避和振荡抑制机制, 实现多机器人障碍环境下的安全编队. 最后, 与现有安全编队方法进行对比仿真和实验验证, 结果表明该方法在嵌套运动饱和约束下可显著提升编队的平滑和安全性能.
- 分布式移动机器人编队 /
- 嵌套运动饱和 /
- 动态安全围栏 /
- 低触发势能函数 /
- 自适应振荡抑制
Abstract: Mobile robots are actually constrained by nested saturation of velocity and acceleration, and they are more likely for such nested motion saturation to be triggered by mobile robots interconnected in a formation under a reactive evasion safety mechanism, thus causing severe formation oscillations. Hence, the study of smooth, safe cooperation and adaptive oscillation suppression methods in such conditions is necessitated. In this paper, mobile robots in a distributed network are taken as the research subjects. Initially, a low-trigger potential function based on line-of-sight and velocity is constructed, enabling collision avoidance while maintaining proximity under the repulsive action of nearby formation robots. A safety acceleration envelope that allows robots to navigate around obstacles is introduced, and it is combined with low-power, low-trigger potential for close-range repulsion, avoiding collisions with non-cooperative obstacles. Secondly, a composite adaptive auxiliary dynamic system is embedded to smooth the trajectory oscillations caused by nested motion saturation and safety acceleration triggered during the evasion process; a distributed formation controller under a composite nonlinear feedback framework is designed, integrating composite evasion and oscillation suppression mechanisms to achieve safe formation of multiple robots in an obstacle environment. Finally, comparative simulations and experimental validations with existing safe formation methods are conducted, and the results demonstrate that this method can significantly enhance the smoothness and safety performance of the formation under nested motion saturation constraints.
- Distributed mobile robot formation /
- nested motion saturation /
- dynamic safety geofencing /
- low-trigger potential function /
- adaptive oscillation suppression

HTML全文

图 1 多机器人分布式控制框图

Fig. 1 Multi-robot distributed control framework

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图 2 基于势场的安全协同机制

Fig. 2 Safety coordination based on potential fields

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图 3 所提出方法编队控制结果

Fig. 3 The formation control results of Proposed

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图 5 Sharma2020方法编队控制结果

Fig. 5 The formation control results of Sharma2020

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图 4 Sharma2020AW方法编队控制结果.

Fig. 4 The formation control results of Sharma2020AW.

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图 6 多机器人集群平台

Fig. 6 Multi-robot cluster platform

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图 7 编队平面轨迹对比

Fig. 7 Formation plane trajectory comparison

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图 8 编队误差对比

Fig. 8 Formation error comparison

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表 1 编队平滑对比指标

Table 1 Formation smoothness comparison index

对比指标	Proposed	Sharma2020
第一次躲避跟随者振荡幅值(m)	0.15	0.90
第一次躲避跟随者恢复时间(s)	6.20	—
第二次躲避领导者振荡幅值(m)	0.21	0.52
第二次躲避领导者恢复时间(s)	4.20	11.5
第二次躲避跟随者振荡幅值(m)	0.07	1.20
第二次躲避跟随者恢复时间(s)	0.00	——

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