Connectivity Preservation and Collision Avoidance in Multi-Agent Systems Using Model Predictive Control

被引:6
|
作者
ElHamamsy, Ahmed [1 ]
Aghili, Farhad [2 ,3 ]
Aghdam, Amir G. [1 ]
机构
[1] Concordia Univ, Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada
[2] Concordia Univ, Mech Ind & Aerosp Engn, Montreal, PQ H3G 1M8, Canada
[3] Space Explorat Directorate Canadian Space Agcy, Quebec City, PQ, Canada
来源
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING | 2023年 / 10卷 / 03期
基金
加拿大自然科学与工程研究理事会;
关键词
Navigation; Sensors; Network topology; Multi-agent systems; Collision avoidance; Predictive control; Trajectory; multi-agent systems; obstacle avoidance; path planning; predictive control; AUTONOMOUS FLOCKING; NAVIGATION; CONSENSUS;
D O I
10.1109/TNSE.2023.3234720
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents an innovative predictive control scheme based on a potential field in order to maintain the connectivity of a flock of agents in a leader-follower configuration with dynamic topology. We consider a group of agents navigating in an environment with obstacles towards their target. The followers avoid collisions with each other and obstacles without using any communication links. It is also required to maintain connectivity with the leader, which is unidentified to the followers. The potential field is dynamically updated by introducing time-varying weighted links between the followers to preserve connectivity as we assume only the leader knows the target position. The values of these weights are adjusted continuously according to agents' trajectories by which the critical neighbours of each agent are determined. The superior performance of the proposed predictive controller for navigation of agents to quickly reach their target is demonstrated comparatively by simulation.
引用
收藏
页码:1779 / 1791
页数:13
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