Dimitrios V. Lyridis

About

Dimitrios V. Lyridis is a leading researcher in maritime robotics and intelligent transportation systems, with a primary focus on unmanned surface vehicle (USV) path planning. His work centers on developing advanced swarm intelligence algorithms, particularly Ant Colony Optimization (ACO) variants, to solve complex multi-objective navigation problems under real-world constraints. His most influential contribution is the 2021 paper "An improved ant colony optimization algorithm for unmanned surface vehicle local path planning with multi-modality constraints," which has garnered 135 citations and established a new benchmark for adaptive, constraint-aware navigation in dynamic maritime environments. Expanding on this, his 2022 comparative study (84 citations) systematically evaluated ACO approaches for multi-objective USV path planning, providing critical insights for algorithm selection in autonomous maritime operations. Lyridis also introduced the Swarm Intelligence Graph-Based Pathfinding Algorithm Based on Fuzzy Logic (SIGPAF) in 2021 (27 citations), which uniquely integrates fuzzy logic with swarm intelligence to handle uncertainty in multi-objective scenarios. Collectively, his research has significantly advanced the practical deployment of autonomous surface vehicles by enabling safer, more efficient route planning in complex, obstacle-rich environments.

Research Focus

Key Achievements

Top Papers

1. 1
   An improved ant colony optimization algorithm for unmanned surface vehicle local path planning with multi-modality constraints

   135 citations · 2021
2. 2
   A comparative study on Ant Colony Optimization algorithm approaches for solving multi-objective path planning problems in case of unmanned surface vehicles

   84 citations · 2022
3. 3
   A Swarm Intelligence Graph-Based Pathfinding Algorithm Based on Fuzzy Logic (SIGPAF): A Case Study on Unmanned Surface Vehicle Multi-Objective Path Planning

   27 citations · 2021

Key Collaborators

Contact & Links