Jiuyang Yu

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About

Jiuyang Yu is a researcher at the forefront of mobile robotics and intelligent path planning, with a focus on developing algorithms that enable robots to navigate complex, dynamic environments with greater efficiency and safety. His most impactful work, the novel whale optimization algorithm for mobile robot path planning, has garnered 80 citations, demonstrating its significant influence in the field. Yu’s research addresses critical limitations in traditional sampling-based planners, such as the Rapidly-exploring Random Tree (RRT) algorithm, which struggle in narrow and cluttered indoor spaces. In his 2024 paper on APF-IBRRT*, he introduced an improved iterative search strategy that combines artificial potential fields with bidirectional RRT to enhance obstacle avoidance and reduce computational overhead. This work, while recent, promises to advance real-time navigation for autonomous systems. Yu’s contributions are particularly valuable for applications in service robotics, warehouse automation, and search-and-rescue missions, where reliable and efficient path planning is paramount. His ongoing research continues to push the boundaries of bio-inspired and hybrid algorithms, making him a notable figure in the evolution of intelligent robotic navigation.