CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots  

作　　者：MU Jianbin YANG Haili HE Defeng 穆建彬;杨海丽;何德峰(College of Information Engineering,Zhejiang University of Technology,Hangzhou,310023,China)

机构地区：[1]College of Information Engineering,Zhejiang University of Technology,Hangzhou,310023,China

出　　处：《Journal of Shanghai Jiaotong university(Science)》2024年第4期678-688,共11页上海交通大学学报（英文版）

基　　金：National Natural Science Foundation of China(Nos.62173303 and 62273307);Natural Science Foundation of Zhejiang Province(No.LQ24F030023)。

摘　　要：A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.

关 键 词：distributed model predictive control(DMPC) robust control barrier function(RCBF) autonomous mobile robot formation control collision avoidance 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]