AI- Enabled Robot Swarm
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.
Fields of Study & Subjects
Modular Robots and Swarm Intelligence
Distributed Control Multi-Agent Systems
Metaheuristic Optimization Algorithms Research
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 2 March 2026
- Language
- EN