Fating Hong

Papers

Total Citations

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About

Fating Hong is a robotics researcher whose work centers on autonomous navigation, localization, and mapping for mobile robots. His key contributions lie in optimizing robot path planning and enabling robust self-localization in complex environments. In his most cited work (10 citations), Hong introduced a genetic algorithm-based method to automatically select optimal parameters for local path planning, moving beyond traditional trial-and-error approaches to improve robot navigation efficiency. He further advanced the field by implementing the gmapping SLAM algorithm on embedded systems (6 citations), addressing the critical challenge of running computationally intensive mapping algorithms on resource-constrained hardware—a vital step toward practical autonomous vehicles. Hong also developed a global localization system using LIDAR sensors (4 citations) that allows a robot to determine its position anywhere within a known 2D occupancy grid map, even from an unknown starting point. This work on LIDAR-based localization is particularly notable for its efficiency in complex environments. Through these interconnected studies, Hong has made meaningful contributions to the practical deployment of autonomous mobile robots, bridging the gap between theoretical SLAM and path planning algorithms and real-world embedded system constraints.