GEAR Lab

Research

Current research lines in drones, unmanned vehicles, and algorithmic optimization.

Current Research Lines

Our research encompasses drone and unmanned vehicle applications across different domains. In sensor localization, we investigate range-based and range-free algorithms by leveraging flying anchors and Ultra-Wideband (UWB) devices for accurate and scalable solutions. In drone delivery, we design optimal and approximation algorithms for minimizing travel distances in mixed rural-urban areas, including wind effects and hybrid drone-truck systems. In smart agriculture, we address irrigation and pest scouting in vineyards and orchards using robots and drones, with graph-based models such as aisle-graphs. For BVLoS drone flights, we use multi-layer weighted graph models to optimize paths while considering safety and connectivity constraints. We also contribute to drone-based video monitoring, disaster response with learning algorithms, and countermeasures against jamming and spoofing threats.

Agriculture BVLoS Delivery WSN Localization

Agriculture

Smart agriculture applications for orchards and vineyards, including irrigation support, pest scouting, and UAV/robot-assisted monitoring with algorithmic route optimization.

BVLoS

Multi-layer weighted graph models and risk/connectivity-aware algorithms for beyond visual line of sight operations in urban and mixed environments.

Delivery

Optimal, approximation, and heuristic algorithms for last-mile logistics, including hybrid truck-drone systems, wind-aware planning, and mixed Euclidean-Manhattan scenarios.

WSN

Wireless sensor network data collection and communication-aware planning, with energy/storage-constrained UAVs and robust scheduling strategies.

Localization

Range-based and range-free localization algorithms using flying anchors, directional antennas, and UWB technologies for accurate and scalable positioning.