Christos Skliros

Iceland GeoSurvey, Comparative Aircraft Flight Efficiency Foundation

Papers

Total Citations

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About

Christos Skliros is a researcher at the forefront of autonomous systems and computational intelligence, with a primary focus on multi-objective path planning for unmanned aerial vehicles (UAVs). His work addresses critical challenges in mission-critical applications, from fire detection to smart delivery services, by integrating advanced algorithms with real-world operational constraints. Skliros’s most cited paper, "A Genetic Algorithm enhanced with Fuzzy-Logic for multi-objective Unmanned Aircraft Vehicle path planning missions" (2022, 22 citations), introduces a novel hybrid approach that combines evolutionary optimization with fuzzy decision-making to navigate complex, multi-objective environments. This work stands out for its practical applicability in swarm robotics, where energy efficiency, safety, and constraint satisfaction are paramount. In his related study on "UAV path planning for offshore swarm-based missions" (2022), Skliros extends these principles to maritime contexts, emphasizing sophisticated decision-making mechanisms for coordinated swarm behavior. Though early in his citation trajectory, his contributions are gaining traction for bridging theoretical optimization with deployable solutions. Skliros’s research is particularly notable for its emphasis on fuzzy-logic-enhanced genetic algorithms, offering a robust framework for autonomous systems operating under uncertainty—a key enabler for next-generation UAV swarms in logistics, surveillance, and disaster response.