Mikhail Martynov
Skolkovo Institute of Science and Technology, Russian Space Systems
Papers
4
Total Citations
48
H-Index
4
About
Mikhail Martynov is an emerging robotics researcher whose work sits at the dynamic intersection of autonomous aerial systems, morphogenetic robotics, and multi-agent coordination. His research focuses on developing next-generation unmanned aerial vehicles (UAVs) capable of operating intelligently across complex, unstructured environments — pushing the boundaries of what drones can physically and cognitively accomplish. Martynov's most recognized contribution, UAV-VLA (2025, 22 citations), introduces a Vision-Language-Action system that integrates satellite imagery with large language models like GPT to enable intuitive, natural-language-driven aerial mission planning — a significant leap toward accessible human-robot interaction at scale. His SwarmGear and MorphoGear projects (2023, 11 and 8 citations respectively) demonstrate a compelling engineering vision: drones that can land on uneven surfaces, traverse rough terrain using adaptive multi-limb morphologies, and operate as heterogeneous swarms with extended endurance. Complementing this, MorphoLander (2023, 7 citations) applies reinforcement learning to coordinate drone groups landing on a morphogenetic leader UAV, enabling sophisticated multi-robot deployment in challenging field conditions. With a growing citation record and a consistent focus on real-world robotic deployability, Martynov represents a promising voice in the future of intelligent, adaptive aerial robotics.
Research Focus
Key Achievements
Top Papers
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