| Title | Swarm Intelligence in Robotics for Disaster Response and Search-and-Rescue Operations |
| Research Area | Swarm Intelligence |
| Abstract | Natural and man-made disasters such as earthquakes, floods, fires, and industrial accidents pose significant challenges to emergency response teams due to unpredictable environments and limited accessibility. Robotic systems have increasingly been deployed in disaster response to support search-and-rescue operations and risk assessment. Swarm Intelligence, inspired by the collective behavior of social organisms such as ants, bees, and birds, offers a decentralized and scalable approach to coordinating multiple robots in complex environments. This paper presents a comprehensive study of swarm intelligence-based robotic systems for disaster response applications. The paper examines swarm algorithms, communication models, and coordination strategies, highlighting their effectiveness in enhancing coverage, robustness, and adaptability. Experimental studies and simulations indicate that swarm-based robotic systems improve search efficiency by 30–45% compared to single-robot approaches. The paper also discusses implementation challenges and future research directions for real-world deployment. |
| Keywords | Swarm Intelligence, Robotics, Disaster Response, Search and Rescue, Multi-Robot Systems, Collective Behavior |
| Paper Status | Published |
| Volume | 2 |
| Issue | 2 |
| Published On | 03/01/2026 |
| Published File |
IJSRTD_4875.pdf
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