Congestion control algorithms for robotic swarms with a common target based on the throughput of the target area

Passos, Yuri Tavares and Duquesne, Xavier and Soriano Marcolino, Leandro (2023) Congestion control algorithms for robotic swarms with a common target based on the throughput of the target area. Robotics and Autonomous Systems, 159. ISSN 0921-8890

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Abstract

When a large number of robots try to reach a common area, congestions happen, causing severe delays. To minimise congestion in a robotic swarm system, traffic control algorithms must be employed in a decentralised manner. Based on strategies aimed to maximise the throughput of the common target area, we developed two novel algorithms for robots using artificial potential fields for obstacle avoidance and navigation. One algorithm is inspired by creating a queue to get to the target area (Single Queue Former — SQF), while the other makes the robots touch the boundary of the circular area by using vector fields (Touch and Run Vector Fields — TRVF). We performed simulation experiments to show that the proposed algorithms are bounded by the throughput of their inspired theoretical strategies and compare the two novel algorithms with state-of-art algorithms for the same problem (PCC, EE and PCC–EE). The SQF algorithm significantly outperforms all other algorithms for a large number of robots or when the circular target region radius is small. TRVF, on the other hand, is better than SQF only for a limited number of robots and outperforms only PCC for numerous robots. However, it allows us to analyse the potential impacts on the throughput when transferring an idea from a theoretical strategy to a concrete algorithm that considers changing linear speeds and distances between robots.

Item Type:
Journal Article
Journal or Publication Title:
Robotics and Autonomous Systems
Additional Information:
This is the author’s version of a work that was accepted for publication in Robotics and Autonomous Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Robotics and Autonomous Systems, 159, 2023 DOI: 10.1016/j.robot.2022.104284
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1706
Subjects:
ID Code:
177926
Deposited By:
Deposited On:
21 Oct 2022 10:25
Refereed?:
Yes
Published?:
Published
Last Modified:
22 Nov 2022 11:57