B.V. Gurenko
Papers
1
Total Citations
1
H-Index
1
About
B.V. Gurenko is a robotics researcher whose core expertise lies in motion planning and pathfinding algorithms for autonomous systems operating in two-dimensional environments. Their most cited work, a comprehensive 2022 study, systematically reviews and analyzes the strengths and limitations of major planning approaches—including Voronoi diagrams, probabilistic roadmaps, rapidly exploring random trees, Dijkstra, A*, D*, and artificial potential fields. This contribution provides a valuable taxonomy for researchers selecting appropriate algorithms for mapped environments, bridging theoretical foundations with practical implementation considerations. While still early in their career, Gurenko’s synthesis of classical and modern path planning methods offers a clear entry point for students and engineers tackling navigation challenges in robotics. The work’s single citation to date reflects its recent publication, but its thorough comparative analysis positions it as a useful reference for those seeking to understand trade-offs between computational efficiency, optimality, and robustness in two-dimensional motion planning.
Research Focus
Key Achievements
Top Papers
- 1STUDY OF PATH PLANNING METHODS IN TWO-DIMENSIONAL MAPPEDENVIRONMENTS1 citations · 2022