Baswani Pavan

Rajiv Gandhi University of Knowledge Technologies

Papers

Total Citations

H-Index

About

Baswani Pavan is a researcher in swarm intelligence and bio-inspired robotics, with a focus on multi-agent systems for environmental sensing and signal source localization. His most cited work, "Butterfly Inspired Multi-robotic Swarm for Signal Source Localization" (2017), introduces a novel meta-heuristic algorithm—Butterfly Mating Optimization (BMO)—that mimics the cooperative mating and foraging behaviors of butterflies to guide a robotic swarm toward a target signal source. This contribution bridges the gap between biological swarm models and practical multi-robot coordination, offering a decentralized, scalable approach to tasks like hazardous plume tracking or search-and-rescue operations. With 3 citations, the paper has laid groundwork for further exploration of Lepidoptera-inspired algorithms in robotics. Pavan’s research underscores how subtle biological mechanisms—such as pheromone-based communication and adaptive local search—can be translated into efficient, robust robotic behaviors. His work is particularly relevant for students and researchers interested in swarm intelligence, nature-inspired optimization, and the design of autonomous, cooperative robotic systems for real-world localization challenges.