Jun Dong Lee
Papers
2
Total Citations
9
H-Index
2
About
Jun Dong Lee is a robotics researcher specializing in autonomous exploration and mapping for mobile robots operating in unknown environments. His work addresses fundamental challenges in simultaneous localization and mapping (SLAM), particularly the computational and memory overheads that arise when robots must build detailed representations of unfamiliar spaces. Lee’s most cited paper, “A Low Overhead Mapping Scheme for Exploration and Representation in the Unknown Area” (2019, 6 citations), tackles the inefficiency of traditional grid maps, which require vast numbers of cells for high-resolution mapping. He proposes a more memory-efficient approach, enabling robots to explore and represent areas with reduced computational burden. In his subsequent work, “Internal and External Frontier‐Based Algorithm for Autonomous Mobile Robot Exploration in Unknown Environment” (2021, 3 citations), Lee advances navigation strategies by developing a frontier-based method that balances internal and external exploration cues, optimizing both coverage and efficiency. While his citation counts are modest, his contributions are technically significant for researchers working on resource-constrained robotic systems and real-time SLAM applications. Lee’s research is particularly relevant for field robotics, where autonomous agents must operate without prior maps or external infrastructure.
Research Focus
Key Achievements
Top Papers
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- 2