Decentralized flocking of multi-agent system based on MPC with obstacle/collision avoidance

被引：0

作者：

Huang, Dapeng ^{[1
]}

Yuan, Quan ^{[1
]}

Li, Xiang ^{[1
]}

机构：

[1] Fudan Univ, Dept Elect Engn, Adapt Networks & Control Lab, Shanghai 200433, Peoples R China

来源：

PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC) | 2019年

关键词：

multi-agent system; flocking control; obstacle avoidance; collision avoidance; model predictive control;

D O I：

10.23919/chicc.2019.8865184

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Most of the literature on flocking of multi-agent system with obstacle/collision avoidance make essential distinction between agents and obstacles. This paper proposes a decentralized model predictive flocking algorithm, and addresses the problems by defining obstacles as special agents, which enables agents to effectively evade external obstacles and to avoid colliding with neighbors while forming a stable a-lattice structure. We not only numerically verify the effectiveness of the algorithm with 50 agents in the MATLAB, but also achieve obstacle avoidance of ten UAVs on a software-in-the-loop simulation platform.

引用

页码：5587 / 5592

页数：6

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