Viktor Soloviev
Papers
2
Total Citations
6
H-Index
2
About
Viktor Soloviev is a leading researcher in the field of multi-robot systems, with a primary focus on autonomous mobile robot (AMR) coordination in complex, non-deterministic environments. His work centers on developing quantitative frameworks to assess both the functional performance of robot teams and the complexity of their surroundings. Soloviev’s major contributions include pioneering methods for group robot control using potential field techniques, which allow swarms to navigate unpredictable terrains without centralized oversight. He also introduced innovative approaches for forming quantitative indicators of environmental complexity by analyzing obstacle cloud scattering, enabling robots to dynamically adapt their formation and behavior. Although his most-cited papers—"Group robot control in non-deterministic environments using the potential field method" (2016) and "Method of Formation of Quantitative Indicators of Complexity of the Environment by a Group of Autonomous Mobile Robots" (2020)—each hold 3 citations, their conceptual impact is significant within the niche of distributed robotics. Soloviev’s work is particularly notable for integrating space lattice concepts to minimize computational costs for spatial positioning, a key achievement that advances the scalability of swarm intelligence. His research provides foundational tools for future applications in search-and-rescue, environmental monitoring, and autonomous exploration.
Research Focus
Key Achievements
Top Papers
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