Emil-Ioan Voisan
Papers
6
Total Citations
99
H-Index
5
About
Emil-Ioan Voisan is a prominent researcher in robotics and computational intelligence, specializing in nature-inspired optimization algorithms for autonomous mobile robot navigation. His work centers on developing and applying metaheuristic algorithms—including Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Charged System Search (CSS)—to solve complex path planning and control problems. Voisan’s major contributions include pioneering off-line and adaptive optimization approaches for multi-robot path planning in static environments, as well as integrating fuzzy logic for robust tracking control. His 2020 paper on GWO-based path planning and fuzzy PI control has garnered 43 citations, reflecting its significant impact on the field. Additionally, his 2013 work on GSA- and PSO-based multi-robot path planning (21 citations) and his 2015 ROS-based framework for robot navigation and human interaction (18 citations) demonstrate his versatility in bridging theoretical optimization with practical robotic applications. Voisan’s research has laid foundational groundwork for collaborative human-robot systems, with his algorithms enabling efficient, adaptive navigation in indoor environments. His ongoing contributions continue to shape the development of intelligent, autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2Multi-robot GSA- and PSO-based optimal path planning in static environments21 citations · 2013
- 3ROS-based robot navigation and human interaction in indoor environment18 citations · 2015
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