Robust decentralised navigation of multi-agent systems with collision avoidance and connectivity maintenance using model predictive controllers
Robust decentralised navigation of multi-agent systems with collision avoidance and connectivity maintenance using model predictive controllers
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DOI：
10.1080/00207179.2018.1514129
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发表时间：
2020-06-02
影响因子：
2.1
通讯作者：
Dimarogonas, Dimos, V
中科院分区：
文献类型：
--
作者：
Filotheou, Alexandros;Nikou, Alexandros;Dimarogonas, Dimos, V
研究一类二阶不确定非线性多智能体系统在有界工作空间中的导航控制问题，该工作空间是静态障碍物的子集。特别是，我们提出了一种分散的控制协议，使得每个代理在工作空间中到达一个预定义的位置，同时基于有限的感知半径使用本地信息。该方案保证初始连接的代理始终保持连接状态。此外，通过引入一定的距离约束，保证了智能体之间的避碰，以及与障碍物和工作空间边界的避碰。在存在干扰和不确定性的情况下，采用分散式非线性模型预测控制器（DNMPC）。最后，仿真结果验证了所提框架的有效性。
This paper addresses the problem of navigation control of a general class of 2nd order uncertain nonlinear multi-agent systems in a bounded workspace, which is a subset of , with static obstacles. In particular, we propose a decentralised control protocol such that each agent reaches a predefined position at the workspace, while using local information based on a limited sensing radius. The proposed scheme guarantees that the initially connected agents remain always connected. In addition, by introducing certain distance constraints, we guarantee inter-agent collision avoidance as well as collision avoidance with the obstacles and the boundary of the workspace. The proposed controllers employ a class of Decentralized Nonlinear Model Predictive Controllers (DNMPC) under the presence of disturbances and uncertainties. Finally, simulation results verify the validity of the proposed framework.