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基于领导者的多群体水下机器人聚集。

Leader-Based Flocking of Multiple Swarm Robots in Underwater Environments.

机构信息

System Engineering Department, Sejong University, Seoul 05006, Republic of Korea.

出版信息

Sensors (Basel). 2023 Jun 2;23(11):5305. doi: 10.3390/s23115305.

DOI:10.3390/s23115305
PMID:37300030
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10256109/
Abstract

Considering underwater environments, this paper tackles flocking of multiple swarm robots utilizing one leader. The mission of swarm robots is to reach their goal while not colliding with a priori unknown 3D obstacles. In addition, the communication link among the robots needs to be preserved during the maneuver. Only the leader has sensors for localizing itself while accessing the global goal position. Every robot, except for the leader, can measure the relative position and the ID of its neighboring robots by utilizing proximity sensors such as Ultra-Short BaseLine acoustic positioning (USBL) sensors. Under the proposed flocking controls, multiple robots flock inside a 3D virtual sphere while preserving communication connectivity with the leader. If necessary, all robots rendezvous at the leader to increase connectivity among the robots. The leader herds all robots to reach the goal safely, while the network connectivity is maintained in cluttered underwater environments. To the best of our knowledge, our article is novel in developing underwater flocking controls utilizing one leader, so that a swarm of robots can safely flock to the goal in a priori unknown cluttered environments. MATLAB simulations were utilized to validate the proposed flocking controls in underwater environments with many obstacles.

摘要

考虑到水下环境，本文针对利用单个领导者的多群机器人的聚集问题进行了研究。群机器人的任务是在不与先验未知的 3D 障碍物碰撞的情况下到达目标。此外，在机动过程中需要保持机器人之间的通信链路。只有领导者才有传感器来定位自己并获取全局目标位置。除了领导者之外，每个机器人都可以通过使用近距离传感器（如超短基线声定位（USBL）传感器）来测量相对位置和相邻机器人的 ID。在提出的聚集控制下，多个机器人在 3D 虚拟球体内聚集，同时保持与领导者的通信连接。如果需要，所有机器人都会在领导者处会合，以增加机器人之间的连接。领导者引导所有机器人安全到达目标，同时在杂乱的水下环境中保持网络连接。据我们所知，我们的文章在开发利用单个领导者的水下聚集控制方面是新颖的，以便一群机器人可以在先验未知的杂乱环境中安全地聚集到目标。MATLAB 仿真用于验证在有许多障碍物的水下环境中提出的聚集控制。

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本文引用的文献

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Optimized flocking of autonomous drones in confined environments.优化自主无人机在封闭环境中的集群行为。
Sci Robot. 2018 Jul 18;3(20). doi: 10.1126/scirobotics.aat3536.
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An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems.多智能体系统事件触发一致性的最新进展概述。
IEEE Trans Cybern. 2018 Apr;48(4):1110-1123. doi: 10.1109/TCYB.2017.2771560.
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Flocking algorithm for autonomous flying robots.用于自主飞行机器人的群聚算法。
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