M.A. Vasileva

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About

M.A. Vasileva is a researcher specializing in autonomous navigation and motion planning, with a particular focus on path planning algorithms for two-dimensional mapped environments. Her work provides a comprehensive review and analysis of established planning methods, including Voronoi diagrams, probabilistic roadmaps, rapidly exploring random trees, and classical search algorithms such as Dijkstra, A*, D*, and their modifications, as well as artificial potential field approaches. Vasileva’s major contribution lies in systematically evaluating these techniques to identify their strengths and limitations in structured environments, offering valuable guidance for researchers and engineers developing robotic navigation systems. Her 2022 study, "Study of Path Planning Methods in Two-Dimensional Mapped Environments," has garnered 1 citation, reflecting its foundational role in synthesizing knowledge for future advancements. While her citation count is modest, her work serves as a critical reference for understanding the landscape of motion planning algorithms, making it a useful resource for students and practitioners entering the field of autonomous systems and robotics.