Yu Kai Gao

Papers

Total Citations

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About

Yu Kai Gao is a researcher whose work centers on intelligent robotics and autonomous navigation, with a particular focus on path planning algorithms for mobile robots. His most notable contribution, the 2013 paper "Path Planning of Mobile Robot Based on Improved Potential Field," has garnered 33 citations, reflecting its influence in advancing obstacle avoidance and trajectory optimization. Gao’s key innovation lies in refining the artificial potential field method to address common limitations such as local minima and goal unreachability, offering more efficient and reliable navigation solutions for dynamic environments. This work has practical implications for autonomous vehicles, warehouse logistics, and service robotics. While his citation count may be modest, the paper serves as a foundational reference for researchers seeking to enhance real-time robotic movement. Gao’s research underscores a commitment to bridging theoretical algorithms with real-world application, making his contributions valuable for students and engineers exploring mobile robot autonomy.