Gao Zhong-guo

Papers

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About

Gao Zhong-guo is a researcher in mobile robotics, with a primary focus on path planning and obstacle avoidance. His key contributions center on improving the classic artificial potential field (APF) method, a widely used technique for robot navigation. In his most cited work, "The dynamic path planning research for mobile robot based on artificial potential field" (2011, 23 citations), Gao introduced a dynamic velocity potential field model and integrated a quantum particle swarm optimization algorithm to enhance real-time path planning in changing environments. This work addresses critical limitations of traditional APF, such as local minima and oscillations near obstacles. In a related study (2011, 7 citations), he further analyzed and proposed solutions to the "goal unreachable" problem and oscillation issues, offering a refined model that improves navigation reliability. While his citation counts are modest, these contributions are foundational for researchers seeking to adapt APF for dynamic and complex environments. Gao’s work is particularly valuable for students and engineers working on autonomous navigation systems, as it provides practical enhancements to a core algorithm in mobile robotics.