Gun-Young Park

Papers

Total Citations

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About

Gun-Young Park has made foundational contributions to mobile robot navigation and path planning, with a particular focus on enabling autonomous operation in unknown and unstructured environments. His most cited work, “Application of RRT-based local Path Planning Algorithm in Unknown Environment” (2007, 18 citations), advanced the application of the rapidly-exploring random tree (RRT) algorithm—a cornerstone technique in robotics known for efficiently exploring large, obstacle-dense spaces. Park demonstrated how RRT could be adapted for local, real-time path planning, a critical step toward practical deployment of autonomous robots in dynamic settings. In a complementary line of research, Park explored novel sensor fusion techniques, as seen in “Application of optical flow to sonar image for mobile robot navigation” (2008). There, he proposed using optical flow methods to process ultrasonic sensor data, overcoming the inherent angular uncertainty of sonar to estimate relative obstacle velocity. This work addressed a long-standing limitation in low-cost robotic perception. While his citation counts reflect a focused, early-career impact, Park’s contributions are notable for bridging theoretical path planning algorithms with practical sensor processing—a combination essential for robust field robotics. His research remains relevant for students and engineers working on autonomous navigation in GPS-denied or sensor-limited environments.