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Robot Platooning Strategy for Search and Rescue Operations

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Abstract

Major abrupt-onset cataclysmic events such as earthquakes, storms, floods, etc., typically damage infrastructure, cause injury, trap numerous individuals, and result in a massive death toll. A prompt life-saving response is required to rescue those who are marooned or trapped under debris. The difference between life and death can be a matter of how fast search and rescue attempts are carried out. On the other hand, these life-saving search and rescue operations are faced with real-time dynamic changes in the disaster site, in addition to possible communication network failure. This paper proposes a novel vision-based robot platooning algorithm that is capable of maneuvering teams of search and rescue robots in a dynamic disaster site, under the worst-case scenario of no available communication network. The algorithm was tested to drive teams of Pioneer-P3Dx and Jackal robots in five real different challenging disaster sites. The proposed algorithm showed enough robustness in all experiments to adapt to the dynamic environmental changes and drove the platoon to the desired destinations even when the team leader was lost.

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All data generated or analyzed during this study are included in this published article.

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Funding

No funding was received for conducting this study.

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Authors and Affiliations

  1. University of Detroit Mercy, Detroit, MI, USA

    Melvin P. Manuel, Mariam Faied, Mohan Krishnan & Mark Paulik

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  1. Melvin P. Manuel
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  2. Mariam Faied
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  3. Mohan Krishnan
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  4. Mark Paulik
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Correspondence to Melvin P. Manuel.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Manuel, M.P., Faied, M., Krishnan, M. et al. Robot Platooning Strategy for Search and Rescue Operations. Intel Serv Robotics 15, 57–68 (2022). https://doi.org/10.1007/s11370-021-00390-7

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  • DOI: https://doi.org/10.1007/s11370-021-00390-7

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