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About

Irina Karpova’s research focuses on decentralized swarm robotics, bio-inspired collective behavior, and local communication mechanisms for homogeneous robot groups. Her major contributions include developing algorithms for leader election and hierarchical role distribution in static swarms, demonstrating that purely local interactions can transition a swarm into an organized collective with control structures. Her 2015 paper on leader election algorithms (28 citations) is her most cited work, alongside a foundational study on forming control structures in static swarms (9 citations) that proposes the local revoting algorithm. Karpova also explores novel mechanisms for managing aggressive behavior in robot groups, drawing inspiration from eusocial insects like ants to resolve resource conflicts. Her work on pseudo-analog communication (2016) addresses decentralized group management challenges, while her 2021 study on animate orientation uses the red forest ant (*Formica rufa*) as a model for route following and collective foraging. By integrating biological principles with robotics, Karpova advances the understanding of scalable, decentralized swarm intelligence, offering practical solutions for autonomous multi-robot systems.