Yue Tusi

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About

Yue Tusi is a leading researcher in mobile robotics and autonomous navigation, with a focus on path planning algorithms that balance efficiency and safety. Their most-cited work, "Using ABC and RRT algorithms to improve mobile robot path planning with danger degree" (2016, 13 citations), introduces a novel hybrid approach that integrates Artificial Bee Colony (ABC) optimization with Rapidly-exploring Random Trees (RRT) to enhance route selection in obstacle-dense environments. By incorporating a "danger degree" metric, Tusi's algorithm enables robots to dynamically assess environmental hazards, ensuring safer and more efficient trajectories from start to goal. This contribution addresses a critical challenge in robotics—navigating complex, unpredictable terrains—and has influenced subsequent studies in autonomous systems. Tusi's research demonstrates a commitment to practical, real-world applications, bridging theoretical optimization with tangible robotic performance. Their work continues to inspire advancements in intelligent navigation, making them a notable figure in the field of mobile robotics and artificial intelligence.