Evangelos Psomiadis

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About

Evangelos Psomiadis is a researcher advancing the frontiers of autonomous robot navigation, with a focus on path-planning in complex, information-constrained environments. His work bridges geometric and semantic understanding, enabling robots to operate more intelligently in unknown or mixed 3D spaces. In his highly cited 2024 paper, "Communication-Aware Map Compression for Online Path-Planning" (4 citations), Psomiadis tackles a critical challenge: how mobile robots can efficiently compress and share local maps to assist teammates in reaching targets without overwhelming communication bandwidth. This framework optimizes the trade-off between map fidelity and transmission cost, a key enabler for multi-robot coordination. His 2025 work, "HCOA*: Hierarchical Class-Ordered A* for Navigation in Semantic Environments" (1 citation), introduces a novel hierarchical search algorithm that leverages semantic class ordering to navigate safely while minimizing computational overhead—a breakthrough for robots operating in environments with task-specific constraints, such as avoiding certain object types. Psomiadis’s contributions are shaping the next generation of autonomous systems, where robots must not only perceive but also communicate and reason about their surroundings efficiently.