Mikhail Chuvatov
Papers
2
Total Citations
7
H-Index
2
About
Mikhail Chuvatov’s research focuses on the coordination and motion planning of multi-robot systems, with a particular emphasis on heterogeneous groups that combine ground rovers and aerial drones. His work addresses the computationally expensive challenge of distributing tasks and optimizing trajectories in real-time robotic operations. In his most cited paper (2017, 5 citations), Chuvatov introduced an evaluation function for the cost of transport operations, enabling efficient target distribution among robot groups without the need to calculate every possible trajectory. This approach significantly reduces computational overhead in dynamic environments. His subsequent work (2019, 2 citations) developed a novel survey algorithm for heterogeneous robot teams, leveraging a modified A* pathfinding algorithm to optimize trajectories by path length. This algorithm allows ground and aerial robots to coordinate their actions seamlessly, improving overall mission efficiency. Chuvatov’s contributions are particularly valuable for applications in search-and-rescue, environmental monitoring, and autonomous exploration, where rapid, scalable coordination is critical. Though his citation counts are modest, his work lays important groundwork for practical multi-robot systems, offering computationally tractable solutions to real-world coordination problems.
Research Focus
Key Achievements
Top Papers
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- 2