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

doi:10.1007/s12204-024-2747-7

Abstract

Abstract: 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 connectivitymaintenance. 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.

Key words: distributed model predictive control (DMPC), robust control barrier function (RCBF), autonomous mobile robot, formation control, collision avoidance

摘要： 针对不确定扰动环境下自主多移动机器人系统的安全编队问题，设计了一种基于鲁棒控制屏障函数（RCBF）的分布式模型预测控制（DMPC）方法。首先，分析系统在编队过程中的安全性要求，并将其归为避碰和距离连通性保持两部分。基于避碰和连通性保持要求分别设计RCBF约束，并组合得到安全约束。然后，将所设计的安全约束与自主多移动机器人编队控制目标相结合，得到优化问题，并与DMPC方法结合以实现安全编队控制。最后，提出RCBF-DMPC算法，在满足约束和期望目标的前提下，保证算法的迭代可行性和稳定性。并通过仿真实验验证了所设计算法能够满足协同编队要求且保证系统安全性。

关键词: 分布式模型预测控制，鲁棒控制屏障函数，自主移动机器人，编队控制，避碰

CLC Number:

TP273

MU Jianbin^∗ (穆建彬), YANG Haili (杨海丽), HE Defeng (何德峰). CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(4): 678-688.

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