AI- Enabled Robot Swarm

In disaster affected areas, unstable debris, blocked access, and a lack of real-time information frequently make search and rescue efforts more difficult. This paper proposes a centrally coordinated AI-enabled robot swarm to locate survivors in dangerous environments to facilitate safe and quick exploration. Compact robots with short-range wireless communication and necessary sensing units make up the swarm. To ensure effective area coverage and less overlap, a central control system gathers information from individual robots, uses AI-based decision algorithms to process environmental information, and sends out coordinated movement commands. This centralized method makes it easier to assign tasks, allows for global situational awareness and preserves structured movement patterns in cramped or collapsed areas. When compared to single robot exploration techniques, prototypes testing shows better search efficiency, obstacle negotiation, and efficient mapping. The findings demonstrate how centralized swarm control can improve search and rescue operations dependability, speed, and safety.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-02
DOI
https://doi.org/10.5281/zenodo.18887478
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
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article

AI- Enabled Robot Swarm

Savitha A C, A. Ariani Hesti Wulan S., Akshay HS, Bharat N et al.
Zenodo (CERN European Organization for Nuclear Research)
Robotics and Sensor-Based Localization
article

AI- Enabled Robot Swarm

Savitha A C, A. Ariani Hesti Wulan S., Akshay HS, Bharat N, Chandra Puneeth Reddy, Advaitha Kiran
article en

Abstract

In disaster affected areas, unstable debris, blocked access, and a lack of real-time information frequently make search and rescue efforts more difficult. This paper proposes a centrally coordinated AI-enabled robot swarm to locate survivors in dangerous environments to facilitate safe and quick exploration. Compact robots with short-range wireless communication and necessary sensing units make up the swarm. To ensure effective area coverage and less overlap, a central control system gathers information from individual robots, uses AI-based decision algorithms to process environmental information, and sends out coordinated movement commands. This centralized method makes it easier to assign tasks, allows for global situational awareness and preserves structured movement patterns in cramped or collapsed areas. When compared to single robot exploration techniques, prototypes testing shows better search efficiency, obstacle negotiation, and efficient mapping. The findings demonstrate how centralized swarm control can improve search and rescue operations dependability, speed, and safety.

Zenodo (CERN European Organization for Nuclear Research)
JSS Academy of Higher Education and Research (IN)
Climate action
Openalex Percentile: Top 33%
Robotics and Sensor-Based Localization
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AI- Enabled Robot Swarm — Savitha A C, A. Ariani Hesti Wulan S., et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS