Online configuration identification of the reconfigurable flight array based on distributed consensus protocol

Purpose Modular reconfigurable robots can deliberately assemble into diverse configurations to adapt to complex environments, making accurate configuration identification essential for automation. This paper aims to develop and experimentally validate a distributed configuration identification framework for the Reconfigurable Flight Array (RFA), a modular reconfigurable aerial robot composed of identical flight unit modules. Design/methodology/approach To achieve distributed configuration identification of the RFA, this study integrates hardware design, information routing and distributed consensus-based computation. Each flight unit module is equipped with a dedicated communication circuit that enables local data exchange with directly connected neighbors. An information routing strategy is developed to allow each module to obtain the relative coordinates of its adjacent modules within its own coordinate frame. And a consensus protocol is implemented to enabling all modules to collaboratively reconstruct the complete RFA configuration with local information. Findings Experimental results verify that the proposed framework enables each RFA module to autonomously and accurately determine its relative position within the overall structure. Flight tests further demonstrate that RFAs with correctly identified configurations achieve significantly improved tracking performance. Originality/value The proposed method enables fully decentralized configuration identification, greatly enhancing system scalability and autonomy. The demonstrated improvements highlight the method’s practical applicability and its potential to advance the intelligent autonomy and cooperative capabilities of modular robot systems.

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Publication Details

Journal
Industrial Robot the international journal of robotics research and application
Published
2026-01-02
DOI
https://doi.org/10.1108/ir-09-2025-0305
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Online configuration identification of the reconfigurable flight array based on distributed consensus protocol

Han Guo, Xiufeng Zhang, Zheng Zhang, Weicheng Zhou et al.
Industrial Robot the international journal of robotics research and application
Modular Robots and Swarm Intelligence
article

Online configuration identification of the reconfigurable flight array based on distributed consensus protocol

Han Guo, Xiufeng Zhang, Zheng Zhang, Weicheng Zhou, Chunxi Yang
article en

Abstract

Purpose Modular reconfigurable robots can deliberately assemble into diverse configurations to adapt to complex environments, making accurate configuration identification essential for automation. This paper aims to develop and experimentally validate a distributed configuration identification framework for the Reconfigurable Flight Array (RFA), a modular reconfigurable aerial robot composed of identical flight unit modules. Design/methodology/approach To achieve distributed configuration identification of the RFA, this study integrates hardware design, information routing and distributed consensus-based computation. Each flight unit module is equipped with a dedicated communication circuit that enables local data exchange with directly connected neighbors. An information routing strategy is developed to allow each module to obtain the relative coordinates of its adjacent modules within its own coordinate frame. And a consensus protocol is implemented to enabling all modules to collaboratively reconstruct the complete RFA configuration with local information. Findings Experimental results verify that the proposed framework enables each RFA module to autonomously and accurately determine its relative position within the overall structure. Flight tests further demonstrate that RFAs with correctly identified configurations achieve significantly improved tracking performance. Originality/value The proposed method enables fully decentralized configuration identification, greatly enhancing system scalability and autonomy. The demonstrated improvements highlight the method’s practical applicability and its potential to advance the intelligent autonomy and cooperative capabilities of modular robot systems.

Industrial Robot the international journal of robotics research and application
Kunming University of Science and Technology (CN), Kunming University (CN)
Openalex Percentile: Top 99%
Modular Robots and Swarm Intelligence
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