Michael Shavin

Skolkovo Institute of Science and Technology

Papers

Total Citations

H-Index

About

Michael Shavin is a researcher specializing in autonomous robotics and precision agriculture, with a focus on the mathematical and computational challenges that underpin modern farming automation. His work addresses some of the most pressing problems in agricultural robotics, including path planning, motion control, obstacle detection, and collision avoidance for wheeled autonomous systems. Shavin's most notable contributions include developing rigorous mathematical frameworks for navigation and control in precision farming environments. His 2021 paper, "Navigation and Control Problems in Precision Farming," laid important theoretical groundwork by formally defining key design challenges in autonomous agricultural systems. This was followed by his 2022 study on motion control of autonomous wheeled robots, which advanced practical algorithms for high-accuracy navigation and attitude determination — capabilities essential for resource-efficient, precision-guided fieldwork. Together, these papers have accumulated nearly 10 citations, reflecting growing interest in his interdisciplinary approach that bridges control theory, robotics, and agricultural engineering. For students and researchers entering the fields of agricultural automation or autonomous systems, Shavin's work offers both a strong mathematical foundation and applied insight into the real-world complexities of deploying intelligent robots in dynamic outdoor environments.