Papers
2
Total Citations
49
H-Index
2
About
Doo Seok Lee is a robotics researcher specializing in motion planning for non-holonomic robots—vehicles constrained by their turning radius and direction, such as cars and differential-drive platforms. His work focuses on bridging the gap between discrete grid-based search algorithms and continuous robot kinematics. In his most cited paper, "Improved Analytic Expansions in Hybrid A-Star Path Planning for Non-Holonomic Robots" (2022, 43 citations), Lee systematically refines the hybrid A-star algorithm by enhancing both its forward search phase and analytic expansion phase, enabling smoother, more feasible paths that respect the robot's motion constraints. He further advances the field in "A Path Planning Method Based on Theta-star Search for Non-Holonomic Robots" (2022, 6 citations), where he adapts the any-angle Theta-star algorithm to generate continuous, collision-free waypoints while maintaining line-of-sight constraints. Lee’s contributions are particularly valuable for autonomous driving and mobile robotics, where efficient, kinematically-aware path planning is critical. His work has been cited in subsequent studies on navigation and control, reflecting its practical impact on real-world robotic systems.
Research Focus
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Top Papers
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