Lele Yao

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About

Lele Yao’s research lies at the intersection of robotics, automation, and intelligent control systems, with a particular focus on enhancing the performance and autonomy of industrial machinery. Yao’s early work, notably the 2013 survey on stereo-based navigation for mobile binocular robots, provided a foundational overview of vision-guided locomotion, helping to shape subsequent developments in robotic perception and path planning. This contribution has garnered steady recognition, with 6 citations that underscore its lasting relevance in the field. More recently, Yao has advanced the state of the art in heavy machinery control through a 2024 study proposing a multi-objective optimal control method for the 6-DOF robotic crusher. This work addresses the complex challenge of simultaneously optimizing product quality, energy efficiency, throughput, and equipment wear—a critical step toward smarter, more sustainable mineral processing. By integrating multiple performance metrics into a unified control framework, Yao’s research promises to improve both operational efficiency and equipment longevity. With a career that bridges foundational robotics surveys and cutting-edge industrial optimization, Lele Yao is making impactful contributions to the evolution of autonomous and intelligent robotic systems.