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About

Kyoungmin Lee is a robotics researcher whose work centers on autonomous mobile robot navigation, simultaneous localization and mapping (SLAM), and sensor-based path planning. With a particular focus on practical, cost-effective solutions, Lee has made meaningful contributions to the challenge of enabling robots to navigate real-world environments using affordable sonar sensors rather than more expensive alternatives. Among Lee's most notable contributions is the development of topological navigation algorithms for corridor environments, addressing key challenges such as node identification and obstacle avoidance using sonar data. His 2010 exploration strategy paper and earlier 2006 topological navigation work, together accumulating nearly 30 citations, demonstrate sustained impact in this specialized domain. Lee also proposed the Navigable Voronoi Diagram, an innovative local path planner that extends classical Voronoi-based approaches for autonomous exploration. His work on integrating SLAM with task-based navigation for home environments reflects a pragmatic approach to real-world deployment, while his incremental construction of the Generalized Voronoi Graph (GVG) adapted the framework for robots with limited sensor coverage. Collectively, Lee's research offers accessible, robust solutions that bridge theoretical navigation methods and practical robotic implementation.