Yerubandi Shirdi Swamy

Rajiv Gandhi University of Knowledge Technologies

Papers

Total Citations

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About

Yerubandi Shirdi Swamy is a researcher at the intersection of swarm intelligence, multi-robotic systems, and bio-inspired optimization. His work draws inspiration from biological models to solve complex engineering problems, particularly in signal source localization and cooperative robotics. Swamy’s most cited paper, "Butterfly Inspired Multi-robotic Swarm for Signal Source Localization" (2017), introduces the Butterfly Mating Optimization (BMO) algorithm—a meta-heuristic that mimics butterfly social and mating behaviors to enable efficient, decentralized search in multi-robot swarms. This contribution has garnered 3 citations and stands as a notable early effort in translating butterfly-inspired collective intelligence into practical robotic coordination. Swamy’s research emphasizes how biological principles, such as cooperative survival and swarm dynamics, can be harnessed to improve autonomous systems’ adaptability and efficiency. While his citation count is modest, his work represents a creative bridge between ethology and robotics, offering a foundation for future studies in bio-inspired swarm algorithms. For students and researchers exploring novel optimization techniques, Swamy’s butterfly model provides a compelling example of how nature’s subtle strategies can inform cutting-edge multi-agent systems.