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About

Aliaksei Dadykin is a robotics researcher specializing in cooperative heterogeneous multi-robot systems, with a particular focus on integrating unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) for autonomous navigation and specialized field operations. His work centers on developing intelligent control architectures that enable ground robots and quadcopters to collaborate effectively in unstructured environments. Dadykin’s most influential paper, "Proposed system of artificial Neural Network for positioning and navigation of UAV-UGV" (2018, 20 citations), introduces a neural network system that fuses data from GPS, robot vision, and quadcopter sensors to enable safe, real-time path planning. He further advanced this concept through the design of the Quadcopter Mobile Robotic System (QMRS), which demonstrated obstacle avoidance in the Belarus-132N mobile robot. In a notable applied project, Dadykin explored the use of UAVs equipped with infrared cameras and ground-penetrating radar for cooperative landmine detection, mapping hazardous locations for subsequent ground-vehicle clearance. His research consistently emphasizes multi-level management systems that shift computational load to onboard computers, reducing wireless data transmission and improving operational efficiency. With a growing citation record, Dadykin is establishing himself as a contributor to the practical deployment of cooperative air-ground robotics for safety-critical and exploration tasks.