Robot navigation and formation control using panel and leader–follower methods

This paper proposes an autonomous navigation method for a leader robot based on the panel method. Multi-robot formation control is achieved using a leader-follower approach and is found to be effective in complex obstacle environments. To demonstrate the proposed method, a collision-free path is first planned for the leader robot using the panel method along the streamline direction from the point of departure to the ending point. Next, a multi-robot formation in a complex obstacle environment is established using the leader-follower method. The effectiveness and feasibility of the leader robot and multi-robot formations are verified through both simulation and experimentation.

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Publication Details

Journal
Scientific Reports
Published
2025-12-05
DOI
https://doi.org/10.1038/s41598-025-30254-4
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Robot navigation and formation control using panel and leader–follower methods

Biao He, Jianxiong Zhang, Jian Zhang, Han Qing
Scientific Reports
Distributed Control Multi-Agent Systems
article

Robot navigation and formation control using panel and leader–follower methods

Biao He, Jianxiong Zhang, Jian Zhang, Han Qing
article en

Abstract

This paper proposes an autonomous navigation method for a leader robot based on the panel method. Multi-robot formation control is achieved using a leader-follower approach and is found to be effective in complex obstacle environments. To demonstrate the proposed method, a collision-free path is first planned for the leader robot using the panel method along the streamline direction from the point of departure to the ending point. Next, a multi-robot formation in a complex obstacle environment is established using the leader-follower method. The effectiveness and feasibility of the leader robot and multi-robot formations are verified through both simulation and experimentation.

Scientific ReportsVol. 16(1)
Yangtze Normal University (CN)
Openalex Percentile: Top 56%
Distributed Control Multi-Agent Systems
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