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About

Jung Kyu Park is a robotics researcher specializing in mobile robot navigation, mapping, and path planning. His work addresses critical challenges in autonomous systems, particularly memory efficiency and real-time decision-making. Park’s most cited paper, “A Low Overhead Mapping Scheme for Exploration and Representation in the Unknown Area” (2019, 6 citations), tackles the memory overhead of grid-based maps in SLAM processes, proposing a more efficient representation for embedded systems. His 2025 study, “Fast Path Generation Algorithm for Mobile Robot Navigation Using Hybrid Map” (4 citations), further advances memory-conscious navigation by combining grid and topological maps. Park has also contributed to coverage algorithms for intelligent robots in deadline-constrained scenarios (2010, 2 citations) and UAV collision avoidance using A* search (2019, 2 citations). His research is particularly valuable for resource-limited platforms like cleaning robots and drones, where efficient mapping and navigation are essential. Park’s work bridges theoretical algorithms with practical robotics applications, making him a notable figure in the field of autonomous navigation.