Mikhail Shavin
Papers
1
Total Citations
6
H-Index
1
About
Mikhail Shavin’s research focuses on the intersection of nonlinear control theory and mobile robotics, with particular emphasis on trajectory tracking for wheeled robots operating in complex, uneven terrains. His most cited work, "Attraction Domains in the Control Problem of a Wheeled Robot Following a Curvilinear Path over an Uneven Surface" (2021), addresses a critical challenge in autonomous navigation: ensuring stability and robustness when robots follow curved paths on irregular ground. By rigorously defining attraction domains—the set of initial conditions from which a robot can successfully converge to a desired trajectory—Shavin provides a theoretical framework that bridges control Lyapunov functions and practical path-following algorithms. This contribution is especially valuable for applications in agricultural robotics, planetary exploration, and search-and-rescue operations, where surface irregularities are unavoidable. Though his citation count (6) reflects an emerging career, the work’s foundational nature suggests growing influence as field robotics advances. Shavin’s approach combines rigorous mathematical analysis with real-world constraints, offering engineers clear design guidelines for stabilizing controllers. His research stands out for its systematic treatment of nonlinear dynamics and uneven surfaces—a combination often overlooked in simpler planar models. For students and researchers, Shavin’s work exemplifies how theoretical control insights can directly enhance robotic autonomy in challenging environments.
Research Focus
Key Achievements
Top Papers
- 1