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About

Weikang Cheng is a rising researcher in intelligent robotic manufacturing, with a focus on precision machining and adaptive automation. His work centers on developing advanced algorithms for robotic deburring, multi-sensor calibration, and real-time pose correction, addressing critical challenges in the automated processing of complex industrial components. Cheng’s most cited paper, “A novel trajectory planning method for robotic deburring of automotive castings considering adaptive weights” (2023, 20 citations), introduces an innovative approach that optimizes tool paths by dynamically adjusting weight parameters, significantly improving surface quality and process efficiency. He further advanced the field with a multi-camera joint calibration algorithm (2024, 6 citations) that enhances robot positioning accuracy under variable lighting and error uncertainty, and a real-time pose correction method (2023, 5 citations) that uses normal consistency constraints to register complex workpieces during machining. These contributions demonstrate Cheng’s ability to bridge theoretical optimization with practical industrial applications, making his work highly relevant for researchers and engineers in robotics, computer vision, and automated manufacturing. His growing citation record underscores the impact of his solutions on improving robotic precision and adaptability in real-world production environments.