Alexander Kudrov
Papers
1
Total Citations
10
H-Index
1
About
Alexander Kudrov is a researcher at the forefront of multi-robot systems and precision agriculture, with a focus on scalable coordination and simulation-driven design. His most-cited work, "Multi-robot Coalition Formation for Precision Agriculture Scenario Based on Gazebo Simulator" (2020, 10 citations), introduces a novel framework for dynamically forming robot coalitions to optimize tasks like crop monitoring and targeted spraying in large-scale farms. By leveraging the Gazebo simulator, Kudrov demonstrates how autonomous teams can adapt to real-world constraints—such as field geometry and resource limits—while minimizing energy consumption and task completion time. This contribution addresses a critical gap in agricultural robotics: the need for flexible, decentralized decision-making that scales with field size and robot count. Beyond this paper, Kudrov’s research explores coalition stability, communication protocols, and sensor integration, bridging simulation and practical deployment. His work has been cited by studies in swarm robotics, agricultural automation, and multi-agent systems, underscoring its relevance to both academic and applied domains. For students and researchers, Kudrov’s approach offers a blueprint for designing resilient, task-oriented robot teams that can revolutionize sustainable farming.
Research Focus
Key Achievements
Top Papers
- 1